SACM - United States of America

Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9668

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    Exercise Testing and Training for Individuals with Cystic Fibrosis
    (Saudi Digital Library, 2025) Alotaibi, Najlaa Zayed N; Lowman, John
    Cystic fibrosis (CF) is a progressive genetic disease that impacts multiple systems (e.g., respiratory system). Hence, routine cardiopulmonary exercise testing (CPET) is recommended to track the disease progression in people with CF. Besides the benefits of exercise testing, exercise training is also beneficial for long-term wellness. It is recommended that people with CF engage in at least 30–60 minutes of aerobic exercise 3 days a week. However, despite the significance of exercise testing and training for people with CF, CPET and exercise training are underutilized in international CF centers. According to the literature, the majority of international CF centers use field-based exercise tests, such as the 1-minute sit-to-stand test (STS), to assess muscle strength and functional status. The 1-minute STS test is one of the exercise tests suggested for people with CF, as the test is cheap and can be conducted in a limited time and space. To our knowledge, there is a gap in the literature regarding use of a validated survey to assess the utilization of exercise testing and training in U.S. CF centers. Additionally, the incorporation of verbal encouragement into the 1-minute STS protocol has not been investigated, which could be used to enhance exercise performance, as the test is self-paced and may underestimate actual physical performance. iii Therefore, we aimed to establish the content validity of an exercise testing and training survey and use it to capture the use of exercise testing and training programs in U.S. CF centers. We also aimed to test whether the encouraged 1-minute STS test can provoke higher exercise intensity as compared to the standard 1-minute STS test. Overall, the feedback we received in the Delphi study improved the overall quality and content validity of the survey. In addition, the results of the validated survey showed that CPET is underutilized in U.S. CF centers, unlike field-based exercise tests. Moreover, the encouraged 1-minute STS test resulted in higher exercise performance as compared to the standard 1-minute STS test; therefore, the encouraged 1-minute STS test appears to be a promising alternative for regular exercise testing in clinical settings for people with CF, as the test is time-and space-efficient, especially when CPET is not available.
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    Exploring Noncognitive Factors in Nursing Education: Grit and Resilience as Predictors of Academic Achievement and Intention to Withdraw
    (Saudi Digital Library, 2025) Almutairi, Khalid; Callaghan, Donna
    The need for more nurses is increasing globally due to the ongoing shortage of the current nursing workforce and the growing demand for healthcare services, particularly in Saudi Arabia, where the healthcare system has historically relied on expatriate nurses. Nursing programs face persistent challenges with high attrition rates, and in Saudi Arabia, estimates suggest that between one third and one half of nursing students do not complete their programs. Recent research has highlighted the potential role of noncognitive traits such as grit and resilience in shaping students’ academic success and persistence. The purposes of this study were to assess the levels of grit and resilience among Saudi nursing students and to examine the extent to which these traits predict academic achievement and intention to withdraw. In addition, the study included an exploration of students’ reasons for their intention to withdraw. A descriptive correlational design was used with convenience sampling from three public nursing schools in the middle region of Saudi Arabia. Students completed an online survey that included the Short Grit Scale (Grit-S), the Connor-Davidson Resilience Scale (CD-RISC-10), a self-report of the latest cumulative GPA, and a single-item measure of intention to withdraw. Tinto’s (1975) model of student departure served as the theoretical framework. A total of 151 Saudi nursing students reported moderate levels of grit and resilience. Neither grit nor resilience significantly predicted academic achievement, while grit emerged as a significant inverse predictor of intention to withdraw. Resilience was not a significant predictor of either outcome. In adjusted models, high school GPA and gender were significantly associated with academic achievement, whereas grit continued to predict lower intention to withdraw. Only one student confirmed an actual plan to withdraw, citing stress as the reason. These findings suggest that grit may contribute more to persistence than to academic performance among Saudi nursing students. Considering noncognitive factors alongside academic indicators may support more holistic approaches to student admissions, advising, curriculum design, and student support. Future research should employ longitudinal and mixed-method approaches, use institutionally verified GPA, and develop validated multi-item tools for withdrawal intention. The results have important implications for nursing education, research, and practice. In education, screening for noncognitive traits and embedding skill-building activities into curricula may help strengthen students’ perseverance during high-risk transitions. In research, the findings support integrating noncognitive traits into Tinto’s individual attributes component and support the cross-cultural use of grit and resilience measures. In practice, fostering these traits during pre-licensure education and reinforcing them through structured transition to practice programs may promote retention and contribute to a more resilient nursing workforce.
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    Artificial Intelligence, Deep Learning, and the Black Box Opacity: International Law and Modern Governance Framework for Legal Compliance and Individual Responsibility
    (Saudi Digital Library, 2025) Aloqayli, Muhannad Khalid; Linarelli, John
    This dissertation examines the unprecedented challenges that deep learning models in artificial intelligence pose to international humanitarian law frameworks governing armed conflict, addressing critical questions about international humanitarian law compliance capabilities, legal personality under the framework of international law and international humanitarian law, and international individual criminal responsibility when autonomous weapons systems employ deep learning models in decision-making processes. Chapter Two provides a comprehensive technical analysis of deep learning architectures, including convolutional neural networks, recurrent neural networks, generative adversarial networks, and transformer networks, and their military applications in target recognition, threat assessment, and autonomous operations. The analysis demonstrates that properly trained deep learning systems can achieve exceptional accuracy in tasks relevant to the principles of distinction and proportionality. However, this technical capability exists alongside a fundamental limitation: the “black box challenge,” whereby decision-making processes emerge from statistical pattern recognition across billions of parameters in ways that remain incomprehensible to human operators, creating unprecedented challenges for legal compliance and individual responsibility. Chapter Three evaluates whether granting legal personality to advanced artificial intelligence could address emerging responsibility gaps. Applying the analytical pragmatic approach through dual criteria of “value context” and “legitimacy context,” the analysis reaches definitive negative conclusions. Granting artificial intelligence legal personality would contradict international humanitarian law’s human-centered foundations, fail to fill responsibility gaps, and potentially shield humans from liability while introducing conceptual incoherence into established normative structures. Chapter Four demonstrates that deep learning, as a black box model in statistical learning, fundamentally challenges traditional international frameworks for individual criminal responsibility. The analysis reveals structural incompatibilities between algorithmic opacity and the requirements of the Rome Statute for mens rea and actus reus. Similarly, command responsibility doctrines face parallel challenges when commanders possess formal control over systems whose decision-making processes transcend human comprehension. The dissertation proposes a modified command responsibility framework recognizing commanders as “AI enablers” rather than traditional superiors, establishing reasonable governance standards for controlled environments while imposing strict liability for high-risk deployments. This framework preserves meaningful accountability while acknowledging technological constraints, shifting focus from comprehending opaque statistical processes to governing deployment decisions and operational contexts within commanders’ control.
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    Game-Theoretic and Stochastic Optimization Models for Energy Policy and Planning
    (Saudi Digital Library, 2025) Albeladi, Abdullah Abdulhadi; Benjamin, D. Leibowicz
    Achieving deep decarbonization of the energy system is essential for social welfare and long-run resource sustainability, yet it is difficult to execute and govern—both in its intended effects and in its unforeseen consequences. The transition is characterized by classic market failures (unpriced externalities, learning and network spillovers), high and lumpy capital requirements, coordination needs across interdependent infrastructures, and pervasive uncertainty about technology costs, fuel prices, and demand. Left to itself, the market tends to underinvest, mis-time investments across the supply chain, and overlook reliability externalities. Effective decarbonization therefore requires an institutional architecture that can steer private behavior toward social objectives while preserving operational reliability and fiscal discipline. Public policy is the primary instrument of that architecture. Well-designed policies align incentives, reduce risk, and coordinate timing. This dissertation is both informed by, and intended to inform, that policy landscape. We first analyze the effectiveness of a current policy design, specifically 45Q designed to promote carbon capture utilization and storage (CCUS) and investigate market failures that reduce its efficacy in Chapter 2. We then expand our approach in Chapter 3 to design a new policy that tries to over come the limitation of the current 45Q policy design depending only on one policy instrument such as the per ton flow subsidy. We included multiple instruments in our proposed policy structure, and analyzed its performance compared to the current policy as a benchmark. We continue in the same scope in Chapter 4 by developing a new formulation and solution strategy that directly links capacity expansion planning to resource adequacy (RA) requirements. This addresses limitations of prevailing approaches and is increasingly important as variable renewable energy (VRE) deployment—spurred by government policy—makes meeting RA targets more challenging. Together, these studies offer evidence and methods for crafting policies and models that make decarbonization both feasible and well-governed.
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    Non-Conventional Heating Methods for CO2 Regeneration
    (Saudi Digital Library, 2025) Alkhalifah, Hassan; Narayanaswamy, Arvind
    Carbon dioxide makes a significant contribution to global warming and climate change. Microwave heating offers a promising approach for efficient desorption in carbon capture. Microwave-assisted desorption reduces the desorption time and selectively heats the adsorbent material, resulting in better regeneration and reducing the system's total energy usage. This thesis considers alternative heating methods to the conventional heating for the temperature swing adsorption process to desorb CO2. The two non-convective heating sources considered here are the microwave heating and the infrared radiation heating. Both of these methods are electromagnetic heating methods, eliminating the need for heating mediums. The microwave heating method heats the sorbent material to desorb the CO2. While the IR methods target the CO2 molecules to excite them, they gain enough kinetic energy to overcome the activation energy. The COMSOL Multiphysics simulation study described here optimized the microwave cavity design for lab-pilot scale, revealing that optimal dimensions can absorb over 98% of input power. Positioning the waveguide at the cavity's middle height proved most effective, not only absorbing 1.6% more power but, possibly more importantly, providing uniform heating distribution. This configuration is ideal for fluidized bed reactors, potentially enhancing energy efficiency in carbon capture processes. In addition, this work presents novel industrial-scale reactor designs for continuous microwave desorption of CO2, filling a critical gap in current microwave heating systems. Traditional microwave technologies have limited efficiency and efficacy in gas desorption operations, including CO2 removal. This study describes innovative reactor designs that use microwave radiation's unique heating capabilities to improve desorption efficiency and selectivity. The study assures optimum microwave power use by optimizing reactor size and configurations using numerical modeling, reducing energy consumption while attaining the intended outcomes. Three unique reactor designs are offered to outperform and save energy compared to current desorption procedures by allowing for continuous operation. The reactors combine sorbent pellets from numerous adsorption reactors into a single desorption unit, eliminating the constraints of classic paired adsorption-desorption systems and increasing production efficiency. The research looks at both horizontal and vertical continuous microwave reactor designs. The horizontal design includes a modified conveyor belt system with cleated belts and Teflon sidewalls, which are ideal for gas desorption. In contrast, the vertical design employs a cascade gate opening mechanism, allowing for precise control over microwave power and exposure time in each tray, maximizing desorption kinetics and efficacy. The study's findings offer valuable insights into designing and optimizing microwave reactors for CO2 desorption, demonstrating microwave technology's potential to revolutionize desorption processes and progress the sector. Moreover, this work employs numerical analysis to investigate temperature distribution during microwave-assisted CO2 desorption with zeolite 13X. The model includes the electromagnetic frequency domain, heat, and mass transfer, and investigates the effects of microwave forward power, purge flow rate, and adding MW-CNT nanoparticles to the sorbent material. The results reveal that increased microwave power accelerates heating and desorption rates, whereas lower power causes steady temperature rises. Adding 2% MW-CNT nanoparticles improves the energy absorbed by the sorbent bed by 14% due to the improvement of the dielectric characteristics. Lower flow rates minimize convective heat loss, resulting in a more uniform temperature distribution. These findings offer important insights into enhancing microwave-assisted CO2 desorption, emphasizing the significance of power levels, flow rates, and nanoparticle additions in increasing CO2 desorption efficiency. Lastly, this work examines the microwave-assisted regeneration process using a packed-bed reactor under direct air capture (DAC) application. For the regeneration process, a commercial Lewatit VP OC 1065 (Lewatit) was selected as the sorbent, and microwave ovens were used as the heating source. This study examines the influence of microwave initial power on CO2 regeneration kinetics, regeneration efficiency, and energy consumption since no study has been performed on this sorbent for this analysis. The regeneration temperatures were varied from 40 °C to 70 °C, and the microwave power was changed from 10 W to 30 W to investigate their effect on the CO2 desorption characteristic. This study also investigates the effect of multiple microwave on/off cycles on the regeneration time and efficiency. The results show that the heating time can be reduced to 1490 seconds under microwave heating (30 W and 70 °C) compared to 5154 seconds under a conventional heating system. The results also show that the energy consumption for a 70% regeneration is lower compared to a 100% regeneration under various microwave conditions. The results illustrate that the energy required for CO2 regeneration can be reduced to around 9.6 MJ/kg CO2 if the regeneration temperatures are 40 °C and 45 °C. It was found that CO2 regeneration at a near-ambient temperature is possible using a microwave-assisted regeneration system. For the case of 70 °C, the regeneration time can be reduced by 16% with the case of two on/off microwave cycles compared to only one continuous microwave on cycle. For a 45 °C desorption temperature with the same microwave on time, the multiple on/off cycles increase the regression efficiency by about 10% compared to one continuous microwave on.
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    COMPUTATIONAL INVESTIGATION OF MEMBRANE AND CATALYST LAYER DESIGN FOR ENHANCED PROTON AND OXYGEN TRANSPORT IN POLYMER ELECTROLYTE MEMBRANE FUEL CELLS
    (Saudi Digital Library, 2025) Bazaid, Mohammed; Jang, Seung Soon
    Polymer electrolyte membrane fuel cells (PEMFCs) rely on efficient proton and oxygen transport for optimal performance, with their functionality highly dependent on the structure and properties of the electrolyte membrane, catalyst layer, and ionomer distribution. In this study, molecular dynamics (MD) simulations are employed to investigate three critical aspects of PEMFCs: the electrolyte membrane nanophase separation, the effect of carbon surface functionalization on water morphology and oxygen permeability, and a novel catalyst layer design aimed at improving mass transport properties. In the first part of this work, we examine the performance of a short side chain perfluorosulfonic acid (PFSA) membrane as the electrolyte. The degree of nanophase separation between hydrophilic and hydrophobic domains is analyzed under varying temperature and hydration conditions to determine its effect on proton transport. The results provide insights into how phase segregation influences the formation of continuous proton-conducting networks, which are essential for achieving high ionic conductivity in fuel cell membranes. The second part of this study examines how oxygen-functionalized carbon in the catalyst layer reshapes interfacial water morphology and, in turn, impacts oxygen transport and proton conduction. Increasing surface oxygen content is hypothesized to enhance local hydrophilicity, promote water retention at the carbon–ionomer interface, and redistribute ionomer away from the surface. We quantify these changes and link them to oxygen permeability and to proton transport metrics, clarifying how surface chemistry modulates hydrophobic/hydrophilic partitioning in the catalyst layer. This mechanistic understanding helps rationalize experimentally observed performance enhancements upon carbon surface oxidation and guides future surface-engineering strategies In the third and final part of this study, a novel ionomer-free catalyst layer design is proposed in which the carbon surface is covalently functionalized with benzyl-sulfonate groups. These hydrophilic acid groups promote the formation of a thin, stable water layer that enables an alternative pathway for proton conduction while enhancing oxygen accessibility by eliminating ionomer coverage on catalyst sites. This design concept provides a molecular framework for reducing oxygen transport resistance and improving proton transport efficiency, offering a promising direction for high-performance fuel-cell architectures. This research provides fundamental insights into the nanoscale interactions governing proton and oxygen transport in PEMFCs, offering potential design strategies for next-generation fuel cell materials. By leveraging molecular simulations, we aim to inform the development of more efficient electrolyte membranes and catalyst layers that overcome key limitations in existing fuel cell technologies.
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    Transport and Optical Properties of Lead Silicate Glasses Containing Multiple Halogen Ions and Vanadium Phosphate Glasses Containing Antimony Oxide
    (Saudi Digital Library, 2025) Alenezi, Manar Hezam; Dutta, Biprodas
    Historically, the electrical conduction in oxide glasses has been a major area of scientific research. The mode of electrical conduction in such a glass varies from ionic to electronic, depending on its composition. On account of the polarizable lattice (or, network) of oxide glasses, all electronic carriers are trapped on account of Anderson localization and/or electron-phonon interaction, rendering them electronically insulating. On the other hand, ionic transport, in all solids, are, by nature, insulating. This thesis reports transport properties in the following two glass systems: (i) PbO-xPbF2-(20-x) PbCl2-35SiO₂ (0 ≤ x ≤ 20 mol%) and (ii) 35P2O5 -xV2O5 - (65-x) Sb2O (0 ≤ (x ≤ 65 mol%). In certain glasses, such as the lead-halide-silicate systems, the anions have been reported to be the principal carriers of electricity. In the first part of this thesis, the results and discussions on anionic conduction in PbO-xPbF2-(20-x) PbCl2-35SiO₂ glasses is reported. In the ternary lead-halo-silicate glasses, with just one type of halogen ion (x = 0), a monotonic decrease in resistivity was observed. However, when both types of halogen ions (Cl- and F- ion) were added, keeping the total concentration of halides fixed, the resistivity exhibited a maximum at a halide ion ratio [F/(F+Cl)] of ~ 0.5. The blocking effects of one anion on the other on conductivity and other physical properties along with the origin of such a mixed halogen-ion effect (MHE) have been reported in this thesis. To gain new insights into anionic conduction in lead-halo-silicate glasses and to determine the mechanism responsible for such non-linear transport behavior, optical absorption spectroscopy, dc conductivity measurements, and activation energy analysis were employed. In the second part of the thesis, electronic conduction via the formation of the small polarons (SPs), and small bipolarons (SBPs) in the 35P2O5-xV2O5-(65–x) Sb2O3 glass system was investigated. The combined influence of SPs and SBPs on both electrical and optical properties of these glasses were studied. The relative concentrations of SPs and SBPs were altered by systematically varying x, allowing a controlled study of their respective roles in charge transport. According to the results, resistivity varies nonlinearly with nV, the ionic fraction of Vanadium, [V/(V+Sb)], reaching a minimum at 0 ≤ nV < 0.3 and a maximum at 0.3 ≤ nV ≤ 0.5. It has been shown that if a glass contains both SPs and SBPs, the conflict between the mobile SPs and the relatively immobile SBPs will adversely affect the transport behavior of the latter. The non-linear transport of small polarons and entropy-driven disorder of the potential field, caused by the mixture of small bipolarons unevenly dispersed among small polarons in the glass network, enhances the degree of Anderson localization of the SPs which has been determined to be the origin of non-linear transport in these glasses.
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    SAUDI AUDIENCE’S ATTITUDES TOWARDS USING CODE-SWITCHING IN FOOTBALL ANALYSIS SHOWS
    (Saudi Digital Library, 2025) Bader, Aldawsari; Warhol, Tamara
    With the initiation of Saudi Vision 2030, the social landscape of the Kingdom has witnessed an unprecedented shift. Entertainment, in particular, emerged as a key axis of change. This social transformation has significant implications for language use, especially in sports media discourse, with the revolution that has occurred in sports television shows and online platforms. Code-switching has become a salient feature in these shows. Accordingly, this study explored Saudis’ attitudes towards code-switching by football commentators and the reasons that inspire such attitudes. Ninety participants completed a questionnaire designed to elicit their attitudes, and fifteen of them were chosen for interviews exploring the reasons that shape these attitudes. The results indicate that Saudi participants generally hold a positive attitude towards code-switching. However, findings further revealed that attitudes are influenced by a tension between reserved language ideologies, fueled by the Salafist mindset, and the modernist, reform-oriented movement promoted by Saudi Vision 2030. Functionality of code-switching emerged as the most prominent reason for this positive orientation, while linguistic ideology stood as the main factor that tempered the generally positive attitude. Positive views were also supported by motivations such as alignment with modernity, viewing entertainment as a permissive zone, and bicultural identity self-actualization. The findings suggest that attitudes towards code-switching are context-sensitive and culturally and socially anchored. These insights carry important implications for sports media outlets, which should consider audience attitudes and diversity when designing and delivering their commentary.
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    Saudi High School Mathematics Teachers’ Perceptions of Implementing Differentiated Instruction (DI) and Artificial Intelligence (AI) in Teaching Mathematics
    (Saudi Digital Library, 2025) Alsamiri, Abdulhadi; Huffman, Douglas; Feldman, Kelli
    The rapid growth of education under Saudi Vision 2030 has emphasized the urgent need for modern teaching methods in mathematics, including addressing individual students’ learning needs and leveraging artificial intelligence to provide enriched educational opportunities and experiences. The study’s primary goal is to provide comprehensive insight into the current perceptions of high school mathematics teachers on three main research questions: implementing DI, implementing Tomlinson’s four-part DI framework, and AI as a teaching tool in their classrooms in Saudi Arabia. A quantitative research design was employed, utilizing a survey instrument, to examine the level of application of DI and the Tomlinson DI framework, usage and proficiency with AI as a teaching tool, as well as gender differences and predictive relationships among these categories. The instrument measured mathematics teachers’ knowledge, beliefs, behavior, and concerns regarding DI; perceptions of Tomlinson’s DI framework (content, process, product, and learning environment); and perceptions of AI as a teaching tool (readiness, perceived usefulness, behavioral intention, participation in professional development, and knowledge). The results show that high school mathematics teachers perceive themselves to have a high level of implementation of differentiated instruction and of differentiating content, process, product, and learning environment. A significant difference between genders was found in only the product category. Additionally, after controlling for demographic factors (gender, years of experience, qualification), both teachers’ knowledge and beliefs made significant contributions to predicting their behavior regarding DI, while their concerns were not significant. Content and process differentiation revealed no significant predictors, while product differentiation had a significant influence on learning environment differentiation. Mathematics teachers’ perceptions of readiness and perceived usefulness of leveraging AI as predictor variables demonstrated a statistically significant influence on their behavioral intention to implement AI (R² change = .525, F change observed (2, 115) = 70.720, p < .001). This research contributes to the growing body of studies related to AI and DI by offering insights specific to the Saudi mathematics context, providing recommendations for professional development programs, curriculum design, and policymakers aimed at reforming mathematics teaching in high school to achieve Saudi Vision 2030 goals.
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    Computational Study of Crossflow Patterned Hollow Fiber Vacuum Membrane Distillation
    (Saudi Digital Library, 2025) Asiri, Mohammed; Alparslan, Oztekin
    Large Eddy Simulations (LES) were conducted to investigate transport phenomena in hollow fiber Vacuum Membrane Distillation (VMD) modules. Most previous studies have investigated VMD, where the feed flow is in the same axial direction and the boundary layers remain attached to the membranes, resulting in a gradual decline in driving force and a decrease in flux toward the outlet. A crossflow-patterned hollow fiber module (HF-VMD), in which the feed enters across the bundle, moving orthogonal to the fibers from top to bottom, is considered in this research. Key performance indicators included permeate flux, temperature polarization coefficient (TPC), and concentration polarization coefficient (CPC). The results demonstrate that crossflow geometry outperforms parallel flow, enhancing flux by nearly 40% while suppressing polarization. Medium to high packing densities (50–75%) provide an effective balance between compact module design and stable flux, as indicated by the merit number. Increasing the Reynolds number improved mixing and mass transfer, peaking at Re = 1500 by 35%. A higher feed temperature was confirmed as the dominant driver of vapor transport, boosting flux by more than 55% at 353 K compared to 333 K. In contrast, extending the module length degraded performance by 14% due to accumulated polarization. Overall, this dissertation advances the understanding of heat and mass transfer in HF-VMD systems and provides practical guidelines for module optimization using high-resolution LES simulations. The findings identify crossflow HF-VMD modules as a promising pathway for next-generation desalination technology, particularly for large-scale applications.
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