28 research outputs found
Relating Almutairi’s critical cultural competence model for healthcare providers transitioning to Qatar
No full textHealthcare providers can be enticed to work in the Middle East due to fascinations with the culture, wealth, and opportunities for personal and professional development. Working in multicultural healthcare environments requires addressing complexities with cultural hierarchies, religion, class systems, and gender. It also requires understanding of the region’s history, as well as knowledge about cultural and social norms. The authors use qualitative accounts, from lived experiences to illuminate their transition to work in Qatar. Upon reflection of their experiences, the authors recommend using a Critical Cultural Competence model as a guide for healthcare providers undergoing transition and longer-term adaptation for promoting cultural safety for healthcare providers and their patients. Some authors of this article have previously published “Recommendations for healthcare providers preparing to work in the Middle East: A Campinha-Bacote cultural competence model approach” (Journal of Nursing Education and Practice, 2017). However, after reflecting upon their experiences as nurse educators living in the Middle East, the authors concluded that Almutairi, Dahinten, and Rodney’s (2015) Critical Cultural Competence Model is more suitable for health care providers transitioning to Qatar. This model addresses necessary elements needed to transition to a new culture, but also includes personal narratives and experiences, which maybe helpful to transitioning to work in another culture. Almutairi et al.’s model (2015) reconceptualises and enriches the concept of transitioning to Middle Eastern multicultural contexts. The aim of this paper is to provide recommendations using Almutairi et al.’s Cultural Competence Model to assist healthcare providers in transitioning to work in Qatar. Another aim is to provide guidance for healthcare professional development in multicultural contexts. Discussion as to how the model may foster a more relevant approach will ensue. Experiential knowledge and narratives are threaded throughout the paper to provide a lived account of the use of this Critical Cultural Competence model by healthcare workers, who have transitioned to the Middle East
The outcome of using different surgical modalities and laser therapy in the treatment of small‐ and medium‐sized congenital melanocytic nevi: a systematic review
No full textPreparation and characterization of Poly (Ethylene oxide) (MW 8 K and 20K)/ Silica nanoparticle composites, 2015
No full textPolymeric nanocomposites of poly(ethylene oxide) (PEO) and silica nanoparticle (Si02) were prepared by solution blending using dichloromethane. The goal of the study was to understand the effect of the silica nanoparticle on the morphology of poly(ethylene oxide) and the ability of the poly(ethylene oxide) to disperse the nanoparticle within the matrix. The study focused on the dispersion of the silica nanoparticle (20 run) as filler into poly(ethylene oxide) of molecular weights 8K and 20K. The nanocomposite products were powders.The products were characterized by Fourier Transform Infrared Spectroscopy, X-ray Diffraction, solid-state nuclear magnetic resonance spectroscopy (13C T1prelaxation rates), scanning electron microscopy and differential scanning calorimetry. Differential scanning calorimetry analysis results of the nanocomposites show thermal properties that are different from the individual components. The results show that the crystallinity is slightly reduced on increasing the Si02 nanoparticle loading. Increasing the SiO2 nanoparticles causes an increase in the Tt p relaxation rate of the PEO 8K suggesting effective dispersion of the nanoparticles within the matrix.Overall, the results suggest that the PEO 8K is better at dispersing the nanoparticles within the matrix compared with the PEO 20K
Machine learning methods for diabetes prevalence classification in Saudi Arabia
Get PDFData Availability Statement: Data presented in the paper are available on request from the corresponding author M.F.A.Copyright © 2023 by the authors. Machine learning algorithms have been widely used in public health for predicting or diagnosing epidemiological chronic diseases, such as diabetes mellitus, which is classified as an epi-demic due to its high rates of global prevalence. Machine learning techniques are useful for the processes of description, prediction, and evaluation of various diseases, including diabetes. This study investigates the ability of different classification methods to classify diabetes prevalence rates and the predicted trends in the disease according to associated behavioural risk factors (smoking, obesity, and inactivity) in Saudi Arabia. Classification models for diabetes prevalence were developed using different machine learning algorithms, including linear discriminant (LD), support vector machine (SVM), K -nearest neighbour (KNN), and neural network pattern recognition (NPR). Four kernel functions of SVM and two types of KNN algorithms were used, namely linear SVM, Gaussian SVM, quadratic SVM, cubic SVM, fine KNN, and weighted KNN. The performance evaluation in terms of the accuracy of each developed model was determined, and the developed classifiers were compared using the Classification Learner App in MATLAB, according to prediction speed and training time. The experimental results on the predictive performance analysis of the classification models showed that weighted KNN performed well in the prediction of diabetes prevalence rate, with the highest average accuracy of 94.5% and less training time than the other classification methods, for both men and women datasets.This research received no external funding
Localising color centers in silicon carbide towards quantum technologies
No full textSilicon vacancy (VSi) and divacancy (VSiVC) color centers in silicon carbide (SiC) are prominent candidates for many quantum technologies due to their attractive properties, including optical interfacing, long spin coherence times, near-infrared emission as well as the potential for scalability. Realisation of these color centers-based quantum applications requires a fabrication technique with high positional accuracy and high fabrication yield. Several methods have been employed to create these color centers, including electron and neutron irradiation. They create the color centers at random locations, making it challenging to integrate them into microstructures such as waveguides, nanobeams, and photonic crystals. Using a mask with holes and ion implantation, color centers can be created in a controlled manner. However, the lithography process of the mask causes inconvenience, and the thickness of the mask restricts the depth of implantation. Recently, femtosecond laser writing techniques has been shown to create color centers in wide bandgap semiconductors. This mask-less method offers three-dimensional positioning accuracies of the order of hundreds of nanometers has been successfully used to create nitrogen vacancy (NV) color centers in diamond while maintaining excellent optical and spin properties. Therefore, this PhD research explores the use of this controllable fabrication method for forming color centers in the highly promising quantum device material SiC and, in particular, the near-infrared VSi and VSiVC color centers formed in this material. The thesis reports on work done to optimise the optical properties of these two color centres, including the investigation of thermal annealing conditions.
The first objective of this thesis is to create VSi color centers in a SiC substrate using a femtosecond laser writing tool as a controllable fabrication technique. A variety of laser pulse energies were employed to create square array grids with VSi color centers positioned at varying depths (from the surface to 10 μm below the surface) for different array positions. VSi color centers created exhibit bright and stable emission depending on the pulse energy of the femtosecond laser. The fluorescence lifetime measurements from the created color centers revealed that the longest lifetime was observed at the depth of 10 μm with the lowest laser energy, while the shortest lifetime was observed at the surface with the highest laser energy.
Following the successful creation of VSi color centers, the author of this thesis then explores the creation of the complex color center with double vacancy (VSiVC color centers) using the femtosecond laser writing method. In this stage, the creation of VSiVC color centers required the additional step of thermal annealing following the laser writing process. A bright and stable emission from the created VSiVC color centers is observed depending on the pulse energy of the femtosecond laser. Localisation accuracy was achieved within approximately 208 nm of the desired position in the transverse plane and a depth of about 700 nm below the surface of the sample.
In the final stage of this thesis, the author extends his investigation on the effect of the thermal annealing temperature on the VSi and VSiVC color centers created by femtosecond laser writing. SiC substrates have been thermally annealed at temperatures in the range from 500 °C to 1000 °C, following the laser writing process. The annealing study demonstrated that the maximum PL intensity of VSi color centers was measured after annealing at 600 °C and that of the VSiVC color centers after annealing at 800 °C.
Overall, the author has succeeded in establishing several important results in the course of this PhD research, including the creation of the VSi and VSiVC color centers in SiC at high positioning accuracy. Detailed investigations of the thermal annealing of VSi and VSiVC color centers in SiC will contribute to a better understanding of how to optimize their optical properties for quantum applications. It is expected that the results of this PhD research will contribute to the development of SiC color centers-based quantum technology applications
Adjusted instruments for evaluating the efficiency of implementing knowledge management systems
Get PDFThe present paper aims to present the results of a scientific research based on application of DeLone and McLean model, for evaluating the efficiency of implementing a knowledge management system into a Romanian university. The model was made operational according to the suggestions of the author and was adjusted to the realities of the higher education institutions.knowledge management, efficiency, DeLone and McLean model
Bullous Pemphigoid Patients and Associated Malignancies: Retrospective Study; Riyadh – Saudi Arabia
Get PDFObjectives The purpose of this study is to describe the prevalence of bullous pemphigoid (BP) and to determine the associated malignancies with BP in Saudi Arabia.Methods Data on patients aged more than 18 years old, who were diagnosed with BP, were retrospectively reviewed. Patients’ sociodemographic, clinical symptoms and associated medical conditions were collected. Data were analyzed using the statistical package for social sciences, version 21 (SPSS, Armonk, NY: IBM Corp.).Results Our sample was composed of 83 patients who were diagnosed with bullous pemphigoid; their mean age was 80.3 years. 3.6 per cent of our patients had drug-induced BP. 97.6 per cent of our patients had comorbidities, such diabetes, hypertension, and dementia. The most commonly encountered co-morbidities were hypertension in 79.51 per cent patients (n=66) followed by diabetes in 51.80 per cent patients (n=43), and heart disease in 33.73 per cent patients (n=28). None of the patients had malignancies, except for 2.4 per cent patients (n=2) who had lymphoma. Conclusion No clear association between BP and malignancies, age group, gender, or other comorbidities was identified. We recommend larger prospective studies to investigate the association between BP and malignancies
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Cost-effectiveness of Favipiravir in moderately to severely ill COVID-19 patients in the real-world setting of Saudi arabian pandemic referral hospitals
No full textPurpose: We aimed to evaluate the cost effectiveness of Favipiravir treatment versus standard of care (SC) in moderately to severely ill COVID-19 patients from the Saudi healthcare payer perspective. Methods: We used the patient-level simulation method to simulate a cohort of 415 patients with moderate to severe COVID-19 disease who were admitted to two Saudi COVID-19 referral hospitals: 220 patients on Favipiravir and 195 patients on SC. We estimated the incremental cost-effectiveness ratio (ICER) of Favipiravir versus SC in terms of the probability to be discharged alive from hospital and the mean time in days to discharge one patient alive. The model was performed twice: first, using unweighted, and second, using weighted clinical and economic data. Weighting using the inverse weight probability method was performed to achieve balance in baseline characteristics. Results: In the unweighted model, base case (probabilistic) ICER estimates favored Favipiravir at savings of Saudi Riyal (SAR)1,611,511 (SAR1,998,948) per 1% increase in the probability of being discharged alive. As to mean time to discharging one patient alive, ICERs favored Favipiravir at savings of SAR11,498 (SAR11,125). Similar results were observed in the weighted model with savings using Favipiravir of SAR1,514,893 (SAR2,453,551) per 1% increase in the probability of being discharged alive, and savings of SAR11,989 (SAR11,277) for each day a patient is discharged alive. Conclusion: From the payer perspective, the addition of Favipiravir in moderately to severely ill COVID-19 patients was cost-savings over SC. Favipiravir was associated with a higher probability of discharging patients alive and lower daily spending on hospitalization than SC. © 2023 The Author(s)Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Integrative Transcriptomic Analysis of GSE65194 and GSE45827 Datasets Identifying Consistent Gene Expression Signatures and New putative Target in Breast Cancer
Get PDFBackground: Breast cancer represents a complex molecular disease with high heterogeneity &mortality rates globally. Despite advances in treatment strategies, understanding the underlying transcriptional alterations remains critical for developing effective therapies. This study conducted an integrative analysis of transcriptomic datasets GSE65194 and GSE45827 to identify consistent gene expression signatures and potential therapeutic targets in breast cancer.Methods: Differential gene expression analysis was performed using GEO2R. The datasets were analyzed for upregulated and downregulated genes using stringent criteria (adjusted p-value 1). Statistical validation included volcano plots, MA plots, UMAP visualization, and Pearson correlation analysis. Gene overlaps were assessed through Venn diagram analysis.Results: Analysis revealed 5,554 differentially expressed genes in GSE65194 (4,968 upregulated, 586 downregulated) and 4,757 in GSE45827 (4,683 upregulated, 74 downregulated). The datasets showed remarkable correlation (r = 0.9992) and 82.8% overlap in upregulated genes. Key genes including COL11A1 (log2FC = 7.69), COL10A1 (log2FC = 7.33), and CXCL10 showed consistent upregulation across datasets. UMAP analysis demonstrated clear separation between cancer and normal samples, validating the distinct transcriptional profiles.Conclusion: The strong correlation between datasets and consistent gene expression patterns identify reliable molecular signatures in breast cancer. The identified genes, particularly those involved in extracellular matrix remodeling and immune response, represent potential therapeutic targets and diagnostic biomarkers. These findings provide a robust foundation for developing targeted therapeutic strategies, though further functional validation is essential for clinical translation.Keywords: Gene Expression Omnibus; Microarray; Affymetrix; Breast Cancer; Venn Diagram; Pearson Coefficien
Nurse Practitioner: Is It Time to Have a Role in Saudi Arabia?
No full textLow recruitment of Saudi nationals into the nursing profession, coupled with a growing population, has led to a severe nursing shortage in Saudi Arabia, particularly of nurses with advanced qualifications in clinical nursing. While the role of nurse practitioner has been successfully integrated into the healthcare systems of the U.S., Canada, the UK and Australia for decades, the advanced practice registered nurse (APRN), which includes nurse practitioners and clinical nursing specialists, is still not being implemented effectively in Saudi Arabia due to a variety of regulatory, institutional and cultural barriers. The author looks at some of those barriers and offers recommendations of how they might be overcome. Given that in many parts of the world, nurse practitioners are considered an essential component to meeting healthcare demands, the author considers the question of whether APRNs can find a role in Saudi Arabia’s healthcare system
