SACM - United States of America
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Item Restricted IMPACT OF STORAGE CONDITIONS AND VARIETAL DIFFERENCES ON THE COMPOSITION, PHYSICAL PROPERTIES, AND FUNCTIONALITIES OF PEAS AND LENTILS(Saudi Digital Library, 2025) Alsaeed, Fatimah; Hall, CliffordPeas (Pisum sativum L.) and lentils (Lens culinaris) are nutritionally rich pulses valued for their high protein, fiber, and starch content. Although their composition and health advantages are widely known, little is known about the effects of long-term storage on their functional qualities and nutritional value. The purpose of this study was to investigate the impact of storage conditions and duration on the proximate composition, physical attributes, and techno-functional traits of lentils and peas. Bin (BIN; -30 to 41°C, 20–98% RH), Non-Environmentally Controlled Warehouse (NECW; -23 to 32°C, 25–84% RH), and Environmentally Controlled Warehouse (ECW; 19–21°C, 50–53% RH) were the three different settings in which yellow peas (Agassiz) and lentils (Richlea) were kept for a maximum of four years. Significant compositional variations were noted over time. Compared to fresh samples, lentils held in BIN conditions had a higher starch content and a lower protein content. After two years of storage at high temperatures and high humidity, both peas and lentils had significant declines in their ability to foam and emulsify. Long-term storage, particularly in BIN and NECW conditions, had flours with higher the water absorption index (WAI) and water solubility index (WSI). Results from RVA pasting indicated that samples held at higher temperatures had reduced final viscosity and gel firmness, indicating a structural breakdown in starch. After four years, color measurements revealed a noticeable darkening of the lentils stored at BIN conditions, which was indicative of enzymatic browning. Temperature, humidity, and storage time had a significant impact on nutrient content and functional characteristics (p < 0.05), as determined by univariate and multivariate analyses (ANOVA and MANOVA). Peas and lentils stored under ECW conditions retained protein content, functionality, and physical properties comparable to the control. Overall, ECW was the most effective condition for preserving the quality of stored pulses, providing valuable insights for improving post-harvest storage practices to ensure the nutritional and functional stability of pea and lentil flours.15 0Item Restricted The Impact of the Codification of the Saudi Evidence Law on the Treatment of Digital Evidence in Saudi Courts(Saudi Digital Library, 2025) Alshammari, Sultan; Schumacher, ScottA crucial element in the process to reach final judgment in Saudi Arabian courts has been the definition of evidence and the determination of its reliability. This persistent problem has been exacerbated by several factors, including the idea that digital evidence is less significant than other forms, the lack of formal regulations for its authentication and reliability, no formal efficient ways of assessing its relevance and admission, and the potential for compromised integrity due to the vulnerability of digital evidence to alteration or falsification. Given that digital evidence is very common in the modern legal environment, it is important to better understand its impact on the length of Saudi Arabian court proceedings. Recognition of the importance of evidence law as a fundamental element of the Kingdom’s Vision 2030 goals for transforming its legal system resulted in a comprehensive 2022 Evidence Law that governs all the means of proof in civil and commercial transactions. Importantly, the utilization and regulation of digital evidence in court proceedings is included in this law, as it marked the first time in Saudi legal history that digital evidence has been formally recognized as an admissible means of proof before the courts. However, despite the 2022 Evidence Law’s promise and capacity to reduce the length of court proceedings, there has been little research that evaluates its role in doing so, particularly in regard to the use of digital evidence. This study sought to gather qualitative data from Saudi legal professionals who are directly involved in the application of the law regarding their experience with the consequences of the 2022 Evidence Law’s impact on the admission of digital evidence, the discretionary power of judges to evaluate such evidence, and the length of court proceedings. then The data were analyzed using Braun and Clarke’s thematic analysis framework. The qualitative method was chosen for this study because direct data collection from legal professionals provided real-world examples of the problem of lengthy court proceedings and the use of digital evidence in the legal proceedings within the context of the 2022 Evidence Law. Findings in this study were that Saudi Arabian legal professionals perceived the new Evidence Law as a major reform that has contributed to less lengthy court proceedings, higher rates of digital evidence admission, and affected the discretionary power of judges in several ways. It has narrowed judges’ discretion in determining admissibility by explicitly specifying which forms of evidence are acceptable. Also, reduced judicial flexibility in granting litigants additional time to submit evidence. At the same time, judges retain authority to assess the weight and the probative value of admitted evidence in relation to the facts of a case. Recommendations for further improvement in the use of digital evidence in court proceedings included making improvements to the Najiz electronic judicial submission platform. Future research opportunities in this topic include comparative studies of the adaptation of the Saudi Arabian 2022 Evidence Law in other Islamic nations, an examination of technological issues in the Najiz system, and an investigation into the potential use of the law in criminal cases. Overall, the study contributed to the growing body of knowledge in English about reforms to the Saudi Arabian legal system, the practical uses of the 2022 Evidence Law, and real-world data about the use of digital evidence in the Saudi courts.20 0Item Restricted EFFECTIVENESS OF FAR-UVC 222 NM ON ESCHERICHIA COLI O157:H7 AND LISTERIA MONOCYTOGENES ACROSS DIFFERENT FRESH PRODUCE SURFACES(Saudi Digital Library, 2025) Bin Murayshid, Abdullah; Yi-Cheng, WangThe objective of this study was to evaluate bactericidal activity of far-ultraviolet C (far-UVC) light at 222 nm against Escherichia coli O157:H7 and Listeria monocytogenes on fresh produce with different surface types and characteristics, romaine lettuce and strawberries. Inoculated samples were treated with increasing far-UVC doses (0–210 mJ/cm²) using a krypton-chlorine excimer lamp. Microbial inactivation was measured as a log CFU/g reduction and surface roughness of each sample was determined by 3D optical profilometry. Far-UVC treatment produced larger reductions on romaine lettuce (2.47 log CFU/g for E. coli; 2.33 log CFU/g for L. monocytogenes) compared to strawberries (1.30 and 1.49 log CFU/g), which was anticipated based on romaine lettuce having a smoother surface (Sa: 3.568 µm) compared to a more rugged strawberry surface (Sa: 36.722 µm). Microbial inactivation showed to be influenced by surface properties. Far-UVC exposures did not significantly affect the CIELAB color parameters taken before and after treatment, which suggested minimal harm to the produce as far as visual quality is concerned. This research contributes to the knowledge about the practical role and usefulness of 222 nm far-UVC to improve microbial safety on fresh produce, while allowing for visual as well as marketable appearance of products without chemical or thermal treatment.17 0Item Restricted THE IMPACT OF NETFLIX’S CONSUMPTION ON THE SAUDI YOUNG ADULTS’ BEHAVIOR, ATTITUDES, AND PERCEPTIONS TOWARDS TATTOOS AND PRE- MARITAL RELATIONSHIPS(Saudi Digital Library, 2025) Khushaim, Mohammed; Simpson, EdgarThis dissertation examines how consumption of Western streaming content via Netflix influences Saudi Arabian young adults’ attitudes toward tattoos and premarital relationships. Tattoos and dating before marriage are traditionally stigmatized in Saudi society, yet rapid social change and Vision 2030 reforms have increased exposure to global media. Drawing on Social Learning and Cultivation theories and broader perspectives of Social Change, Modernization, Cultural Hegemony and Globalization, the study tests whether repeated exposure to streamed representations predicts more progressive attitudes. A cross-sectional survey collected data from 168 Saudi participants aged 18–35. The instrument measured weekly streaming hours, attitudes toward tattoos and premarital relationships on five-point Likert scales, and demographic variables. Descriptive statistics, Pearson correlations and multiple regression were used to test hypotheses; open-ended responses provided qualitative insight. Streaming hours were positively correlated with more accepting attitudes toward tattoos (r = 0.41) and premarital relationships (r = 0.47; both p < 0.01). Attitudes toward tattoos and premarital relationships were themselves correlated (r = 0.53). Regression analyses confirmed that weekly streaming predicts progressive attitudes even after controlling for age, gender and education; the standardized regression coefficients were beta = 0.34 for tattoos and beta = 0.39 for premarital relationships. Age showed a negative association (beta = -0.21), indicating younger respondents were more open, while education had a modest positive effect. Gender was not significant. Despite these associations, survey means show conservative norms remain influential. Only about 28 % of participants agreed that people with tattoos are “great,” and roughly 22 % agreed that premarital relationships are acceptable. Qualitative responses suggest respondents selectively adopt liberal values while maintaining cultural identity. Overall, the findings support social learning and cultivation perspectives by demonstrating that exposure to Western streaming content is linked to more accepting attitudes among Saudi youth, yet traditional values persist. The study adds evidence from a non-Western context and underscores the importance of media literacy and culturally sensitive education as Saudi society navigates rapid change.13 0Item Restricted The Future of Tourism in NEOM: AI-Powered Robot Assistants and Their Impact on Service Workers from the Resource-Based View(Saudi Digital Library, 2025) Althagafi, Rayan; Chang, Hyo Jung (Julie); Blum, Shane; Jones, Robert; Koo, BonhakThis study examines the impact of AI-powered robot assistants on service workers' quality of life in the context of NEOM, designed to be a hub for technology and innovation in Saudi Arabia. While prior research has focused on consumer perceptions and limited geographical regions, this study fills a crucial gap by assessing the influence of AI on employees' quality of life in a limited-researched region. Using a 2 (robot: human-like vs. non-human-like) x 2 (productivity: high vs. low) experimental design, this quantitative study analyzes data from a survey to understand how robot assistants affect value perception, trust, workload reduction, quality of work life, and overall quality of life. One-way ANOVA was used to examine the effect of the stimuli, and Structural Equation Modeling (SEM) was used to test the proposed model. The findings indicate that AI robot assistants positively influence service workers' quality of life by reducing physical and mental workloads reduction, which in turn enhances their quality of work life. While participants expressed a preference for human-like robots, the data consistently showed that high-productivity robots lead to more beneficial relationships with workers, regardless of their form. This aligns with the Computers Are Social Actors (CASA) and Resource-Based View (RBV) theories, confirming that AI can function as a social entity and provide a competitive advantage. The study also found that prior experience with AI systems influences user expectations, leading to a conflict between stated preferences and actual positive experiences. The research contributes to the understanding of anthropomorphism as a multidimensional construct and provides a conceptual model for future research on AI's influence on workers' quality of life. The study recommends that businesses prioritize a robot's functionality and coordinate between tangible and intangible values.16 0Item Restricted An Examination of Utilizing the X Platform in the Context of Indefinite Article Production Among Saudi English Learners(Saudi Digital Library, 2025) Madkhali, Amnah; Braver, Aaron; Borst, Stefanie; McFadden, BrianThe current study aims to investigate the role of integrating the X platform in a linguistic pedagogical setting to enhance specific linguistic features, namely the indefinite article. It follows the theoretical frameworks of Vygotsky’s sociocultural theory (1930), Long’s interaction theory (1996), and the surface structure taxonomy of errors (Dulay et al., 1982). The study utilizes a sequential exploratory research approach that involves both qualitative and quantitative research. In the first stage, a qualitative questionnaire was distributed to English learners at Jazan University to identify learning practices, and an online interview was conducted with Jazan University instructors from two different campuses to examine teaching practices. Following that, a quantitative questionnaire was distributed to the same learners to examine the accuracy of indefinite article, and this questionnaire was later analyzed by the Forced Choice Elicitation Task. The analyses, including a one-way ANOVA and an ANCOVA, were conducted to test the variables, specifically, to examine whether hours on social media (time dedicated to consuming English on social media), type of content, type of interaction, age, gender, and motivation influence the result of the study. The results indicated that while the type of content, gender, and motivation do not affect the result significantly, the hours on social media and type of interaction significantly impact the result, while age shows a marginal effect. The findings of the study suggested first that the learners showed a predictable sequence of types of errors when producing English articles (regulation addition, simple addition, omission, and substitution). Second, the learners who consume English content on the X platform frequently received higher scores (M=19.25) compared to the learners who depend only on classroom instructions (M = 15.9). Third, although educators demonstrated a positive attitude toward integrating social media platforms, the integration of these tools and the encouragement of their students are still insufficient. Therefore, the study suggests adapting online networking in a structured manner to overcome the gap of authenticity in language classrooms.5 0Item Restricted ADVANCED DEEP LEARNING TO GENERATE AND DETECT FAKE IMAGES OF EGYPTIAN MONUMENTS(Saudi Digital Library, 2025) Alaswad, Daniyah; Zohdy, MohamedThis study examined the use of StyleGAN to create synthetic images of Egyptian monuments, addressing a critical gap at the intersection of generative artificial intelligence and cultural heritage. Through extensive experiments on a large dataset containing 5,000 Egyptian monument images, we show that architectural changes to the StyleGAN framework can significantly improve the quality and authenticity of the generated images. Our study contributes to the existing literature. First, we designed an enhanced discriminator architecture incorporating noise injection, squeeze-and-excitation blocks, and an improved MinibatchStdLayer, resulting in a Fréchet Inception Distance 27.5% better than that of the original model. We further introduced a novel image-text alignment approach using SigLIP, which can generate semantically guided monuments. We applied Differential Evolution (DE) to optimize the latent space of the conditional generator to reduce the alignment error by 15% for the targeted monument-generation tasks. We systematically analyzed various truncation methods used to manage noise in generated images by finding the best parameters that fit the architecture best but are also diverse. Statistical validation using bootstrap confidence intervals, McNemar’s test and DeLong’s ROC analysis show significant improvements with effect sizes in the moderate to large range (Cohen’s d ≈ 0.9-1.4) The discriminator was able to achieve 95.5% accuracy with a 5.3% false positive rate and 3.6% false negative rate. This 62% error drop was compared to the baseline. Under heavily corrupted conditions (JPEG quality = 10; Gaussian blur σ = 5.0), it achieved 78-85% of the baseline performance, whereas the default achieved 65-72% of the baseline performance. Frequency domain analysis results revealed resilience, with AUC values generally >0.95, varying by frequency. The new discriminator was approximately 20 to 25 percent more robust to adversarial attacks. However, both architectures are fundamentally vulnerable to stronger attacks. Our research shows how strategic refinements of operations models can produce representations of Egyptian monuments that attain a high-quality and satisfactory level of diversity that we can detect. Innovations can greatly help in the preservation of cultural heritage, virtual tourism, visualization, and education. This study will allow the generation of high-quality and varied Egyptian monument images, which can help in the digital conservation and easy accessibility of one of the world’s great architectural heritages.25 0Item Embargo ROBUST AND ENVIRONMENTALLY-FRIENDLY NANOCOMPOSITES FOR DAYTIME RADIATIVE COOLING(Saudi Digital Library, 2025) Aljwirah, Abdulrahman; Ruan, Xiulin; Chortos, Alex; Boudouris, Bryan; Mie, JianguoRadiative cooling technologies exchange thermal energy with deep space and require no moving parts or energy input. Radiative cooling solutions have been implemented via a variety of innovative approaches within scientific literature. They rely on achieving high solar reflectance and high thermal emittance to obtain a surface temperature below their local ambient temperature, which in consequence can combat climate change and promote passive daytime cooling. Nonetheless, many of the proposed radiative cooling solutions face various challenges in implementing them into real world applications. High-performance ultra-white pigments have produced the first single-layer and metal-free full daytime sub-ambient cooling materials in the form of solvent-based ultra-white radiative cooling Acrylic-paints. However, these radiative cooling Acrylic-paints rely on solvent processing during fabrication, which produces volatile organic compounds (VOCs) that have serious negative impacts on human health and on the environment. The rising concerns of utilizing VOCs have introduced persisting environmental and health regulations across many industries, including the paint manufacturing industry. Moreover, elastomeric coatings are popular in water-proofing and in cool-roof applications, which are also known for their enhanced mechanical robustness. However, commercial white elastomeric coatings contain TiO2 as their white pigment, where no daytime cooling has been reported for elastomeric coatings within the scientific literature. To address these challenges, in this dissertation we have utilized these ultra-white pigments to develop water-based radiative cooling paints that demonstrate full daytime sub-ambient cooling similar to the mentioned solvent-based radiative cooling Acrylic-paints. These paints demonstrate full daytime sub-ambient cooling of 2.7°C, 2.6°C, 2.5°C, utilizing the ultra-white pigments to produce high solar reflectance of 95.4%, 93.7%, and 96.1%, and strong sky window emissivity of 0.932, 0.924, and 0.825, for BaSO4, CaCO3, and hBN paints, respectively. Their hydrophobic performance yield high water contact angles of 118°, 139.9°, and 136.7°, and they achieved the low-VOC classification by recording 26 g/L, 18 g/L, and 30 g/L of VOC content for BaSO4, CaCO3, and hBN paints, respectively. These VOC levels are lower than many commercial water-based paints with VOC content of up to 200 g/L. Furthermore, we have utilized these ultra-white pigments to fabricate environmentally-friendly ultra-white elastomeric coatings (or ultra-white elastomers), with daytime sub-ambient cooling similar to the mentioned solvent-based radiative cooling Acrylic-paints. These ultra-white elastomers recorded total solar reflectance of 95.2%, 94.4%, 94.4%, along with strong sky window emissivity of 0.956 ± 0.001, which recorded average temperatures of 1.9 °C, 2.1 °C, and 1.3 °C below ambient for BaSO4 CaCO3, and hBN ultra-white elastomeric coatings, respectively. These elastomers demonstrated >100% elongation rates, and elastic moduli of 975 psi ± 88 psi, 18.4 ± 0.04 psi, 439 psi ± 13 psi, along with excellent hydrophobicity featuring water contact angles of 137°, 154°, and 144° for BaSO4, CaCO3, and hBN elastomeric coatings, respectively. The cooling performance of our environmentally-friendly ultra-white elastomeric coatings surpasses commercial elastomeric coatings. In summary, this dissertation attempts to advance the development of radiative cooling materials by providing environmentally-friendly and high-performance alternatives to the solvent-based ultra-white radiative cooling Acrylic-paints and to the existing TiO2-based commercial elastomeric coatings. While radiative cooling paints and coatings can provide passive daytime cooling in a scalable approach, producing them with environmental sustainability help accelerate their commercialization process where they can replace the conventional TiO2-based commercial white paints and coating. As a result, these materials add the value of combating the global heating effect and climate change, while also providing additional energy cost savings in producing passive cooling.7 0Item Restricted Resource Efficient Distributed Inference of Deep Neural Networks(Saudi Digital Library, 2025) Mubark, Waleed; Uddin, Yusuf SarwarDeep Neural Networks (DNNs) play a central role in contemporary artificial intelligence, enabling a wide range of applications including computer vision, natural language processing, and multimodal intelligence. Despite their success, deploying these models efficiently on edge devices remains challenging due to substantial computational requirements, energy consumption, and communication overhead. This dissertation proposes an integrated framework for enabling resource-efficient distributed inference of DNNs in Edge AI environments. The framework is structured around three interrelated components: asynchronous split inference, resource-aware batching, and efficient tensor compression between clients and servers. The first contribution introduces an asynchronous split inference approach in which model execution is divided across edge clients and backend servers while overlapping communication with computation. This approach, referred to as ASAP (Asynchronous Split Inference for Accelerated DNN Execution), reduces idle periods during inference and improves system throughput. The second contribution investigates adaptive input and slice batching techniques designed to enhance hardware utilization and reduce inference latency across heterogeneous client devices. These batching strategies dynamically respond to variations in device capabilities and network conditions, enabling efficient resource sharing in distributed settings. The third contribution presents a tensor compression strategy that minimizes communication overhead by compactly encoding intermediate activations exchanged between clients and servers, achieving bandwidth reduction without compromising inference accuracy. Extensive experimental evaluations are conducted using state-of-the-art vision models, including Vision Transformer (ViT), Swin Transformer, DenseNet, and ResNet, under a variety of deployment scenarios. The results show up to a 67 percent reduction in end-to-end inference latency, along with notable improvements in GPU utilization and energy efficiency. By combining asynchronous execution, adaptive batching, and compression techniques, the proposed framework supports scalable, low-latency, and adaptive inference suitable for real-world edge deployments. Overall, this dissertation contributes to the advancement of distributed deep learning by addressing the interplay between computation and communication in heterogeneous edge–server systems. The proposed solutions establish a foundation for future research on adaptive model partitioning, compression-aware inference, and real-time multimodal processing in large-scale Edge AI platforms.28 0Item Restricted Essays on the Economics of Renewable Energy: Cross-Regional Evidence on Labor, Health, and Environment(Saudi Digital Library, 2025) Alqarni, Rania; Avetisyan, MisakThe global energy transition has profound implications for environmental sustainability, labor markets, and public health. While renewable energy adoption is widely promoted as a means to reduce greenhouse gas emissions, its broader socioeconomic impacts remain contested and uneven across regions. This dissertation investigates how renewable energy consumption interacts with employment, environmental outcomes, and health across di- verse economic and institutional contexts. The first study examines the dynamic relationships between renewable energy con- sumption, industrial employment, and CO2 emissions in the world’s top seven carbon- emitting countries from 1990 to 2019. Using a PVAR framework with impulse response functions, the results confirm the renewable energy-led emissions reduction hypothesis: in- creases in renewable energy reduce CO2 emissions over time. However, they also generate short-term declines in industrial employment, reflecting transitional labor market disrup- tions. The second study turns to Sub-Saharan Africa and explores the links among re- newable energy, fossil-based electricity, GDP, CO2 emissions, and maternal mortality from 1990 to 2020. Employing a PVAR model, the findings suggest that renewable energy, dom- inated by traditional biomass, temporarily lowers maternal mortality and CO2 emissions. Yet these benefits are likely driven by external interventions such as aid programs rather than intrinsic advantages of biomass. The results emphasize the need for modern renewable technologies to achieve durable health and environmental gains in the region. The third study investigates the causal impact of renewable energy use, PM2.5 air pollution, and socioeconomic factors on life expectancy in Eastern and Western Europe from 1995 to 2020. To address endogeneity in pollution and macroeconomic conditions, a two-stage least squares (2SLS) estimator with fixed effects is applied, with Driscoll–Kraay vi Texas Tech University, Rania Fahad S. Alqarni, December 2025 estimates used as robustness checks. The results show that PM2.5 exerts a significant neg- ative causal effect on life expectancy in both regions, with larger magnitudes in Eastern Europe. Renewable energy has significant direct effect on Western Europe only once in- strumented, while GDP is a significant determinant of life expectancy in Eastern but not Western Europe. Taken together, the three studies provide cross-regional evidence that the benefits of renewable energy are multi-dimensional but uneven. The findings highlight the need for integrated strategies that link decarbonization with labor market policies, energy access, and air quality regulation. This dissertation contributes to the literature by demonstrating how renewable energy affects not only emissions but also labor and health outcomes, and by emphasizing the importance of region-specific institutional capacity in shaping transition trajectories.3 0