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    Functional Aerogels and Composites for Wastewater Remediation: Targeted Dyes and Antibiotics Adsorption
    Badr, Tendra; Rassy, Houssam; Ghoul, Mazen; Hmadeh, Mohamad; MS; Department of Chemistry; Faculty of Arts and Sciences
    Water pollution is one of the most challenging environmental problems, due to unprocessed wastewater discharge from industries, hospitals, sewage, etc. Antibiotics and organic dyes, stemming from these sources, are pollutants that have damaging effects on human and aquatic life. Due to their high porosity, high surface area and low densities, aerogels and metal-organic frameworks (MOFs) make good candidates as adsorbents in water remediation, tackling these contaminants. This work includes three projects studying different types of these pollutants and adsorbents. The first project focuses on the development of novel metal oxide aerogel/MOF composite materials, prepared via the epoxide-assisted sol-gel process, where different MOFs were incorporated into the sol before the addition of the gelling agent. The synthesized composites were tested for their ability to adsorb various anionic and cationic toxic dyes under different experimental conditions. While the second project investigates the effect of select first-row transition metals on the adsorption capacity and stability of the aerogel network. Here, the sol-gel method was used to synthesize a series of metal-aluminum oxide aerogels, and their performance was evaluated via dye adsorption. Ultraviolet-Visible Spectroscopy was utilized as a primary method for quantification in these two projects. The third project, on the other hand, involves the synthesis of imine-functionalized silica aerogels. Pristine aerogel, prepared using alkoxide precursors, was post-modified by reacting it with a synthesized Schiff base. The adsorption of antibiotics from simulated wastewater onto the synthesized aerogel, under various conditions, was quantified using High-Performance Liquid Chromatography. In all the projects, the aerogels were obtained upon drying the synthesized gels under supercritical carbon dioxide conditions. In addition to kinetics, thermodynamics, and other experimental studies, the structure, porosity, morphology, crystallinity and thermal stability of the synthesized materials were comprehensively characterized using Fourier Transform Infrared Spectroscopy, Nitrogen adsorption-desorption techniques, Scanning Electron Microscopy, X-ray Diffraction, and Thermogravimetric Analysis.
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    Genetic Basis of Short Face Syndrome in Eastern Mediterranean Families
    Chammas, Marc; Ghafari, Joseph; Kurban, Mazen; Macari, Anthony; Nemer, Georges; MS; Department of Dentofacial Medicine; Faculty of Medicine
    Introduction: The short face syndrome reflects a vertical dimension dysmorphology characterized by decreased lower face height, hypodivergent growth pattern, flat mandibular plane, and closed gonial angle. Contributing factors include skeletal dysmorphology and hyperfunction of the masticatory muscles. Aim: To investigate the inheritance pattern and the genes involved in the short face syndrome, explore the genes involved in this vertical dysplasia., and analyze the correlation between this vertical dysplasia and the different sagittal malocclusions. Methods: The sample consists of subjects from 2 families diagnosed with short face syndrome through lateral cephalometric radiographs taken routinely to assess skeletal and dentoalveolar features and corresponding clinical. Upon IRB approval, family members affected and non-affected with the condition consented to have 5cc of blood drawn for genetic testing. Next Generation Sequencing (NGS) was used and a Whole Exome sequencing (WES) was applied to gauge the genetic determinants of the short face syndrome. Results: A Mendelian inheritance pattern was observed segregating in either an autosomal dominant, X-linked manner in family A and autosomal recessive in family B. Pedigree analysis showed equally affected males and females. Extraoral photographs demonstrated that SFS is transmitted with different levels of penetrance. Cephalometric analysis on affected subjects revealed a decreased lower facial height, a hypodivergent facial pattern, and a tendency towards a skeletal class II. Genetic analysis denoted the presence of 4 novel genes affecting skeletal development. Conclusion: This is the first study evaluating the inheritance pattern and genetic contribution to SFS. It illustrated the clinical, cephalometric characteristics of affected individuals and shed light on the genetic map responsible for the development of SFS. It is the first study to evaluate hypodivergence independently of class II,2.
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    Spousal Characteristics and Self-Employment Survival
    Khalil, Charbel; Zalghout , Abdallah; Salti, Nisreen; Abboud, Ali; MA; Department of Economics; Faculty of Arts and Sciences
    This thesis examines the role of spouse-related factors in the self-employment survival process in the United States. While there is a large literature on the implications and determinants of entrepreneurial outcomes, such as individual characteristics, financial resources, and business performance, much less attention has been paid to the household context within which decisions of self-employment are made. The role of marital exposure, spousal income, and spouse-related shocks in explaining the duration of self-employment has not been sufficiently explored. Using data from the Panel Study of Income Dynamics (PSID), this dissertation utilizes a nonparametric, semiparametric, and parametric survival analysis framework to study the association between spouse- related factors and duration of multiple self-employment spells. The main spouse- related variables incorporated in this study are total spouse labor income and marital status. The results of this analysis indicate that spouse labor income impact on self- employment survival is modest. In contrast, marital shocks seem to have a strong effect on survival in spell 1.
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    A Nature-Based Solutions Planning Framework for Arid Cities
    Jaroush, Sarah; Abunnasr, Yaser; Zurayk, Rami; McPhearson, Timon; MSES; Department of Landscape Design and Ecosystem Management; Faculty of Agricultural and Food Sciences
    As aridity continues to increase in the world, with nearly 300 large cities projected to face increasing water scarcity issues by 2050, Nature-based Solutions (NbS) offer a unique multifunctional approach to addressing the severe environmental pressures in these contexts. While existing NbS planning frameworks provide a robust structure and guidance for city-planners, there is a gap in tailoring these frameworks to the context of hot arid cities, given the different environmental and socio-economic conditions. Against this backdrop, this research seeks to answer how can existing NBS planning frameworks be contextualized to address the specific challenges in hot arid cities? The methodology used to answer this question employed a qualitative analysis of existing NbS, Urban Planning and Sustainable Urban Planning frameworks, coupled with a cross-case comparative analysis of implemented NbS interventions in arid cities. Findings reveal a dominance in greening models in NbS, leaning towards addressing visible short-term stressors – like addressing heat stress using increased vegetation– with little consideration to underlying environmental stressors – like limited water supply. This mismatch is exacerbated by limited research engagement to adapt NbS interventions to the local ecosystem processes. The study also reveals how interactions between lead, funding and implementing actors impact NbS design and deployment across different scales and spatial contexts, with city-wide interventions skewed towards centralized governance systems, and smaller-scale interventions comprising higher modes of stewardship and participation with the local community. By synthesizing insights from 94 global case studies and existing planning literature, the study offers a Contextualized NbS Planning Framework (C-NbS-F) for hot arid cities, and a prototype decision-support tool to help planners shift from visible "greening" symptoms to underlying hydrological limits. Lastly, this thesis contributes to enhancing urban resilience against progressing aridification due to climate change, by generating transferable lessons and strategies for a more water-scarce future.
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    Accelerating Graph Isomorphism with GPU-Parallel Canonical Labeling
    Dbouk, Rana; El Hajj, Izzat; Mouawad, Amer E.; Safa, Haidar; MS; Department of Computer Science; Faculty of Arts and Sciences
    Graph isomorphism (GI) is a fundamental problem in computer science with applications across many domains, including chemistry for molecular comparison, pattern recognition in image analysis, and motif discovery in biological networks. Despite its importance, GI remains computationally hard on certain graph classes, where canonical labeling search trees can grow exponentially. This work presents a CUDA based parallelization of the canonical labeling algorithm (nauty), leveraging coarse grained parallelism across the search tree and fine-grained parallelism within nodes using GPU thread blocks. This strategy aims to achieve substantial speedups on structurally hard instances by enabling concurrent exploration of the search space, potentially making canonical labeling practical for graph classes previously considered infeasible. Extensive experimental evaluation on a diverse set of benchmark graph families demonstrates that GPU parallelization substantially reduces runtime, particularly on hard instances. On highly symmetric graph families, the proposed method achieves speedups ranging from approximately 4× to over 10,000× relative to our sequential baseline, and up to several thousand times relative to nauty. In such cases, early pruning enabled by parallel exploration eliminates large portions of the search tree. In contrast, graph families for which the explored search tree remains nearly identical across implementations exhibit consistent speedups of around 18×–23× over the sequential implementation and approximately 3× over nauty. The observed gains are mainly due to parallelizing the core computation within each search node rather than reductions in the search space. Overall, these results demonstrate that GPU-based parallel canonical labeling is both feasible and effective, delivering substantial performance improvements while preserving the algorithmic behavior of classical tools.