SACM - United States of America

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

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Start date: 2024Has files: Yes

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    STRUCTURAL AND MECHANISTIC INSIGHTS INTO USP10 AND USP7: CONFORMATIONAL REGULATION AND INHIBITION STRATEGIES
    (Wayne State University, 2025) Alshammari, Eid Salem; Zhe, Yang
    Ubiquitin-specific proteases USP10 and USP7 play crucial roles in regulating diverse cellular processes and have emerged as attractive therapeutic targets in cancer. In this dissertation, we present a multi-scale structural and molecular dynamics investigation of these deubiquitinases, combining predictive modeling, crystallographic data, molecular dynamics (MD) simulations. For USP10, which lacks a crystal structure, AlphaFold model and MD simulations revealed a stable and highly conserved USP domain, with some flexible loops surrounding the active site and the Ub-binding pocket, suggesting auto-regulatory structural elements that may control conformational regulation, substrate access, and enzymatic activity. USP10’s flexible N-terminal region contains regulatory loops that transiently interact with the catalytic domain, suggesting another layer of regulation and substrate control. Compound GL462 is a potential USP10 inhibitor, exhibiting a binding mode near the active site. Protein stability and inhibition assays confirmed GL462’s destabilizing effect on USP10 through a selective protein unfolding mechanism. Its potent inhibitory activity, positioning it as a promising lead for further development. For USP7, comparative analyses of the apo and ubiquitin-bound structures revealed that proper alignment of the catalytic triad and opening of the switching loop are key elements for USP7 activation. Classical and metadynamics simulations showed that certain mutations in the switching loop, such as H294E, stabilize an active-like state with minimal energy cost, while others, like V302K, remain energetically trapped in either an intermediate or inactive conformation, highlighting the critical role of switching loop dynamics in USP7 activation. Analysis of sixteen USP7-inhibitor complexes identified two distinct binding modes. Mode 1 compounds appear to rigidly block activation by binding to a critical region within the catalytic cleft. In contrast, Mode 2 inhibitors bind at the Thumb-Fingers interface, located at the edge of the ubiquitin-binding pocket, thereby interfering with ubiquitin binding while permitting reversible regulation. Metadynamics simulations revealed distinct energy barriers associated with these inhibitors, correlating with their conformational flexibility and mechanisms of action. Taken together, these findings reveal key structural features regulating USP10 and USP7 conformational activation, regulation, and inhibition, providing a framework for developing targeted inhibitors with therapeutic potential.
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    Cyber Physical Attacks and Detection MEthods in Water Distribution Systems
    (The University of Alabama, 2025) Hameed Addeen, Hajar; Yang, Xaio
    Modern technologies adopt Internet of Things (IoT) devices to increase water management efficiency and enhance water quality services. However, the limitations of IoT devices, such as small sizes and poor security, weaken the Water Distribution System (WDS) security and many attackers compromise the critical components of WDS. Cyber-physical attacks (CPAs) are considered one of the biggest challenges that decrease the security factors in WDS by disrupting normal operations and tampering with the critical data of the water system. Therefore, this dissertation proposes an anomaly detection method to detect cyber-physical attacks and mitigate their bad impacts on the components of WDS. First, we study the current state-of-art for the common cyber-physical attacks and common detection mechanisms for the WDS. Also, we compare CPA attacks and detection methods with emphasis on ideas, methods, evaluation results, advantages, and limitations. Second, we propose a deep learning model based on a conditional variational autoencoder (CVAE) to detect cyber-physical attacks. The CVAE model shows a highly effective way to maximize the chance of generating the desired output and detecting CPA attacks quickly. We also train CVAE on (BATADAL) real medium-sized water distribution dataset and demonstrate high-efficiency results. Experiment results indicate that our proposed method of CVAE can detect all the listed attacks with high accuracy and reduce false alarm issues. Then, we evaluate the proposed models’ performance using various metrics, including accuracy, precision, recall, and F1 score. In addition, we compare the CVAE model with existing models to detect CPA attacks, and the results show that we reach a high accuracy of 98%. Third, we designed an adversarial attack on our CVAE model to show the security risks of this attack and the negative impact on the model’s accuracy. We apply the Fast Sign gradient method to fool the CVAE model and predict the anomalies as normal data rather than anomalies. Then, we propose our novel defense approach, the CVAE defense model, to detect adversarial attacks. The CVAE defense model consists of adversarial detection and the CVAE defense models. The adversarial detection model adopts CNN and LSTM methods to classify data as adversarial or clean. The CVAE defense model takes the output of the adversarial detection model and passes it to our proposed noise generation method. After that, the noise generation method is produced and passed to the CVAE model and activation function. Finally, we calculate the Euclidean distance between the reconstructed output and input vectors and compare it to the threshold. If the output is less than the threshold, there is no attack. Otherwise, the output should be one, and there is an attack. The results show that our CVAE defense model can detect adversarial attacks and increase the performance to an overall 92%.
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    Advanced Mass Spectrometric Strategies for The Selective Detection of Oxidized Lipids
    (University of Toledo Health Science Campus, 2025-08) ALYAMI, MOHAMMED ABDULLAH A; Von Grafenstein, Hermann
    Oxidized lipids are involved in inflammation, immune responses, and disease progression, making their detection important for many fields of biomedical research. However, analyzing the oxidized lipids is difficult because of their low abundance, chemical instability, and suppression by major lipids like phosphatidylcholine (PC) in matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. This dissertation introduces analytical strategies based on selective derivatization and digital filtering to improve detection. Two complementary methods were developed. The first method, Mass-Difference Digital Filter (MDDF), uses stearic acid hydrazide to derivatize aldehyde-containing oxidized phospholipids. It monitors paired signals formed between native lipids and their hydrazones. While MDDF works well under ideal conditions, it becomes less effective when isobaric lipids interfere or when the oxidized lipids are very low in abundance. To solve these problems, the Automated Bell-Curve Selectivity Algorithm (ABSA) was developed. It uses fixed-charge Girard’s reagents (GRT, GRP, and synthesized GRB) to derivatize oxidized lipids. ABSA identifies true hydrazones by detecting a bell-shaped signal pattern across reagent concentrations, where the signal increases during optimal derivatization and decreases due to ion suppression at higher reagent levels. This method successfully detected low-abundance oxidized lipids, even when background phospholipids were present in sixteen-fold excess. In addition, peak shape analysis was performed to improve mass accuracy and signal consistency. Twelve statistical models were tested for fitting MALDI-TOF lipid peaks. The Johnson SU distribution showed the best fit for asymmetric peaks, followed by the Extended Skew Normal and Exponentially Modified Gaussian distributions. Standard symmetric models like the normal distribution did not perform well, confirming that asymmetric models are more suitable for lipid peak shapes. Overall, combining chemical derivatization with digital pattern recognition offers a practical and effective solution for detecting oxidized lipids. These methods reduce the need for complex sample preparation or chromatography and make it possible to selectively identify and quantify oxidized lipid species in complex biological samples.
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    Trends in and Factors Associated with Science Achievement among Fourth Graders in Saudi Arabia: A Secondary Analysis of TIMSS Data
    (Florida institute of technology, 2025-05) Massawe, Reda; Marcinkowski, Thomas
    This secondary analysis examined trends and factors associated with science achievement among fourth-grade students in Saudi Arabia using data from the Trends in International Mathematics and Science Study (TIMSS). Between 2007 and 2019, Saudi students consistently scored below the international average in science, with female students outperforming males by more than 30 points. The study addressed two issues: (1) reasons behind Saudi students’ underperformance and (2) limited research on contributing factors. TIMSS data from 2011, 2015, and 2019 were analyzed using descriptive, correlational, and regression methods. While trends across the years were explored, only 2019 data were used for detailed regression analyses. Science achievement was the dependent variable, with 30 independent variables drawn from student, teacher, school, and home questionnaires. Data were cleaned and prepared through item and scale scoring, outlier detection, and multicollinearity checks. Findings showed that student variables contributed most to science achievement. Peer interactions, science confidence, and home study supports were consistently strong predictors. Teacher and school variables, such as emphasis on science investigation and socioeconomic composition, added modest explanatory power. Home background factors, including pre-primary education and parental occupation, also played a meaningful role. Gender-based analyses revealed differences: for males, science confidence and early education were key, while for females, school socioeconomic context and home supports had stronger effects. Study delimitations and limitations, as well as generalizability and implications were discussed. In addition to offering recommendations for further research, the findings support targeted policies that enhance early learning, peer engagement, and equitable learning environments.
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    SPORT EVENT PRESTIGE CONCEPTUALIZATION: SPECTATOR, PARTICIPANT, AND VOLUNTEER PERCEPTIONS OF VARIOUS SPORT EVENT SIZES
    (University of Florida, 2025) Khan, Hamza; Kaplanidou, Kyriaki
    This study aims to provide a comprehensive conceptualization of sport event prestige by examining the perspectives of various sport consumer groups. Specifically, it seeks to analyze how the various sport event consumers (e.g., sport fans, sport event participants, and volunteers) perceive and interpret the notion of sport event prestige in the context of sporting events. By integrating insights from these diverse groups, the study seeks to develop a precise understanding of the concept of sport event prestige. To achieve this, the study adopted a qualitative methodology, where semi-structured interviews were used to understand the perception of different sport consumer groups on how they define prestige. The results revealed that prestige was defined differently across consumer groups. For participants, prestige was perceived as tied to achievement and sacrifice; spectators emphasized emotional experience and event atmosphere; and volunteers associated prestige with contribution, and future opportunities. Moreover, sport event prestige was found to have impacts beyond the consumer groups, with positive effects observed on the hosting nation's economy and tourism. However, the findings also indicated that the impact of prestige is not always positive, negative impacts associated with the economy and crime were also reported. These insights provide a better understanding of the roles that prestigious sport events play among sport consumer groups and the hosting nation. This study will help sport managers and event organizers seeking to enhance event value and stakeholder engagement by understanding how the term "prestige" functions across different sport event sizes and various stakeholder groups.
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    EVALUATION OF THE SAFETY IMPACTS OF SPEED LIMIT INCREASES ALONG HORIZONTAL CURVES ON RURAL FREEWAYS IN MICHIGAN
    (Michigan State University, 2025) Alsady, Abdullah S; Savolainen, Peter T
    In May 2017, the State of Michigan enacted legislation that increased the maximum posted speed limit from 70 mph to 75 mph on approximately 614 miles of rural limited-access freeways. While previous studies have evaluated the broader operational and safety impacts of this change, limited research has focused on its effects on roadway segments with geometric constraints—particularly horizontal curves. These curves are recognized as high-risk locations due to reduced sight distance, elevated lateral acceleration demands, and speed compliance challenges. This study addresses that gap by assessing the safety impacts of the speed limit increase specifically on horizontal curves. The analysis used crash data spanning five years before (2012–2016) and five years after (2018–2022) the speed limit change. A total of 116 horizontal curve segments were selected as treatment sites, while 81 comparable segments served as controls. Two analytical approach was employed: a cross-sectional regression analysis to identify key predictors of crash frequency and severity, and a before–after evaluation using the Empirical Bayes (EB) method to adjust for regression-to-the-mean and other confounding factors. Site-specific Safety Performance Functions (SPFs) were developed using data from control sites to predict expected crashes across total crashes, fatal and incapacitating injury crashes (KA). The EB analysis revealed a 46.4% statistically significant increase in total crashes across all treatment sites after the speed limit increase. KA crashes rose by 36.5%, though this increase was not statistically significant. In summary, this study provides strong empirical evidence that speed limit increases on horizontal curves can lead to higher crash frequencies. The findings emphasize the importance of incorporating geometric assessments and targeted safety countermeasures—such as advisory speed signs—when modifying speed policies. These insights are especially relevant for transportation agencies seeking to enhance safety while maintaining efficient travel on rural freeway networks.
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    Improving Feature Location in Source Code via Large Language Model-Based Descriptive Annotations
    (Arizona State University, 2025-05) Alneif, Sultan; Alhindawi, Nouh
    Feature location is a crucial task in software maintenance, aiding developers in identifying the precise segments of code responsible for specific functionalities. Traditional feature location methods, such as grep and static analysis, often result in high false-positive rates and inadequate ranking accuracy, increasing developer effort and reducing productivity. Information Retrieval (IR) techniques like Latent Semantic Indexing (LSI) have improved precision and recall but still struggle with lexical mismatches and semantic ambiguities. This research introduces an innovative method to enhance feature location by augmenting source code corpora with descriptive annotations generated by Large Language Models (LLMs), specifically Code Llama. The enriched corpora provide deeper semantic contexts, improving the alignment between developer queries and relevant source code components. Empirical evaluations were conducted on two open-source systems, HippoDraw and Qt, using standard IR performance metrics: precision, recall, First Relevant Position (FRP), and Last Relevant Position (LRP). Results showed significant performance gains; a 40% precision improvement in HippoDraw, and a 26% improvement in Qt. Recall improved by 32% in HippoDraw and 24% in Qt. The findings highlight the efficacy of incorporating LLM-generated annotations, significantly reducing developer effort and enhancing software comprehension and maintainability. This research provides a practical and scalable solution for software maintenance and evolution tasks.
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    ADVANCED OPTIMIZATION TECHNIQUES AND HYBRID MICROGRID DESIGN FOR SOLAR ENERGY INTEGRATION AND MPPT ENHANCEMENT USING MODIFIED FIREFLY ALGORITHM
    (Saudi Digital Library, 2025) Abusaq, Mana; Zohdy, Mohamed
    Present-day, microgrid systems, particularly systems engaging photovoltaic (PV) technologies, are gaining increasing attention as they offer promising solutions for a resilient and sustainable power demand worldwide. Saudi Arabia, with its enormous solar resources, is great positioned to embrace renewable energy alternatives. However, the southern region, particularly Najran Provenience, remains unutilized despite its significant solar potential. This thesis comprehensively investigates the design and sizing of microgrids of this area following enhancing system reliability and optimizing performance using the professional capabilities for the scientific research. The first study examines a grid-connected hybrid microgrid for the Najran Secondary Industrial Institute (NSII) utilizing the Hybrid Optimization of Multiple Energy Resources (HOMER) software. The system integrates PV, battery storage system (BSS), diesel generator (DG) and grid. In this study, the system’s reliability was assessed using the Loss of Power Supply Probability (LPSP). The LPSP was maintained at zero, indicating no unmet load for all scenarios. The design of the grid-connected balances the technological, economic and environmental considerations, insuring the system’s resilience and cost-effectiveness. The second study shifts the focus to an off-grid system. The off-grid solar-powered microgrid interduces a novel approach for sizing the microgrid using a Modified Firefly Algorithm (MFA). This modified algorithm enhances the convergence speed and solution quality which is a significant improvement over the traditional firefly algorithm (FA). The system’s reliability was evaluated under two scenarios, with LPSP values of 0.01 and 0.1. This innovative MFA demonstrated superior performance in optimizing the sizing of the system’s components, particularly in scenarios where reliability is critical. The third study focuses on the impact of partial shading conditions (PSC) on photovoltaic systems and the effectiveness of maximum power point tracking (MPPT) algorithms. A comparative analysis was conducted to evaluate the performance of four MPPT techniques: Perturb and Observe (P&O), Particle Swarm Optimization (PSO), FA, and MFA. The results demonstrate that MFA consistently outperforms the other algorithms in tracking the maximum power point (MPP) under PSCs. Additionally, the study investigates the influence of varying load resistance on the efficiency of MPPT tracking, revealing that MFA exhibits higher adaptability and stability across different conditions. The research findings highlight the importance of employing advanced MPPT techniques to enhance PV system efficiency under challenging environmental conditions. Together, these studies enrich the deployment of renewable energy systems in Saudi Arabia’s southern regions by highlighting the potential of the advance and novel techniques in designing the methodologies of these microgrid. This research, by addressing both grid-connected and off- grid, contributes to the Saudi Arabia’s immense efforts to diversify its energy sources under Vision 2030.
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    INFANT CONTAINERS: A COMPREHENSIVE ANALYSIS OF MOVEMENT AND PLAY AFFORDANCES, DEVELOPMENTAL IMPACT, AND BELIEFS OF CAREGIVERS AND CLINICIANS
    (Saudi Digital Library, 2025) Alghamdi, Zainab Saleh; Michele A. Lobo
    Infant containers (e.g., jumpers, seats, strollers, and car seats) serve practical roles that are important for caregivers. For example, strollers and car seats can be used for transportation, jumpers and exersaucers for infant entertainment, swings for soothing and sleep, and seats and highchairs for feeding. The time that an infant spends in these devices every day can quickly add up: an infant may eat in a highchair, play in an exersaucer, nap in a swing, and ride in a car seat. This may negatively affect infants’ development and health, as these devices can limit infants’ movement and exploration of the environment. The purpose of this dissertation was to examine the association between the use of infant containers and infants’ development and physical activity, and to compare parents’ use and beliefs with therapists’ beliefs and educational practices regarding container use. This work aimed to inform professional recommendations and parent education regarding container use. In Aim 1, we conducted a systematic evaluation of the potential movement and play affordances of several container types and reported on the developmental claims made by the manufacturers. We found that containers vary in the affordances they provide for movement and play, with play gyms and exersaucers offering greater affordances, while car seats and carriers offer considerably fewer. Additionally, many containers had developmental claims made by the manufacturers, especially related to motor development and learning. Aim 2 involved cross-sectional surveys for parents and pediatric therapists to evaluate 1) parents’ use of containers, 2) the beliefs of parents and therapists about the impact of containers on infant development, and 3) pediatric therapists’ educational practices regarding container use. This study revealed that prolonged container use was associated with lower fine motor scores on the Ages and Stages Questionnaire 3rd edition (ASQ-3). Additionally, parents and therapists had significantly different beliefs about containers, and therapists’ recommendations about durations for container use differed from parents’ reported use. Moreover, pediatric therapists indicated different approaches to parent education regarding containers, with most recommending parents limit container use to a specific amount of time per day. Aim 3 was a pilot experiment to evaluate the immediate effects of containers and the floor on infants’ physical activity and to explore infants’ interactions with built-in toys. The container types, identified as having different levels of movement affordances in Aim 1, were the exersaucer, floor seat, and car seat. We found that, overall, infants’ physical activity was the highest in the floor condition compared to the exersaucer, floor seat, and car seat. This dissertation builds on previous research by conducting a comprehensive analysis of the association between container use and infants’ activity and development. It employed a variety of research methods, including content analysis, surveys, and movement analysis with wearable sensors. The findings can enhance parent education regarding containers by identifying gaps between parents’ and pediatric therapists’ beliefs and providing insight into the effects of varying container types on infants’ development and physical activity.
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    Advanced design and optimization of novel fibonacci switched capacitor converters for ultra high efficiency DC-DC power conversion
    (Saudi Digital Library, 2025-04-01) Hawsawi, Mansour Zubair; Zohdy, Mohamed A
    The study explores the design and analysis of two DC-DC converter configurations integrated with solar photovoltaic (PV) renewable energy systems, comparing the conventional boost converter with a novel Fibonacci switched-capacitor (FSC) boost converter. Advanced Maximum Power Point Tracking (MPPT) algorithms, including Perturb and Observe (P&O), Incremental Conductance (INC), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), are paired with both converters to optimize energy extraction from solar PV systems. Simulation results reveal that both converter topologies, when combined with the appropriate MPPT algorithms, effectively maximize power output from the solar PV system.
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