Now showing items 1-20 of 1052

    • Exploring the Co-occurrence of the Two Mangroves Avicennia marina and Rhizophora mucronata in the Red Sea and their Microbiomes

      Baazeem, Azad (2022-09) [Thesis]
      Advisor: Rosado, Alexandre S.
      Committee members: Al-Babili, Salim; Carvalho, Susana
      The mangrove ecosystem is a marginal and complex ecosystem. Mangrove trees can tolerate heat, desiccation, high salinity, radiation, and anoxic conditions. The physiological features of mangroves help them tolerate these stressors, but their relationship with prokaryotic communities also plays a role in a productive mangrove ecosystem, mainly in nutrient cycling and biogeochemical transformation. In Saudi Arabia, a few studies were conducted to understand the microbial communities residing in the mangrove ecosystem. Most of the studies were focused on the sediments or rhizosphere of the most dominant species in the kingdom, Avicennia marina. In this study, the bacterial composition of two mangrove species (Avicennia marina and Rhizophora mucronata) and the relationship between them was explored using next generation amplicon sequencing of the V3-V4 region of the 16S rRNA. In both species, samples from four compartments were collected (sediments, rhizosphere, roots, and leaves). Both species had a similar microbial composition, with Proteobacteria and Chloroflexi being the most dominant phyla in all compartments. The lack of difference in alpha diversity measures (number of ASVs and Shannon-diversity index) between species highlights the symbiotic relationship between the trees. Previous studies have reported that A. marina has a more diverse microbial community than R. mucronata, however this difference was not significant in our samples. The multivariate analysis showed us that the microbial composition of the leaf and root samples was grouped separately from the microbial composition of sediment and rhizosphere samples, highlighting the specific microbial composition of each compartment. In addition, the enriched strains in each cluster were explored and related to the surrounding environment of the mangrove ecosystem, followed by the exploration of unique strains in each compartment using SIMPER analysis. In conclusion, this study provides the first information on the Red Sea Northern mangrove (Al-Wajh region) tree microbiomes, encompassing roots, leaves, rhizosphere, and sediments. Furthermore, by showing that some bacteria can colonize different plant compartments we contribute to disentangling their propagation channels within plants.
    • Experimental and Theoretical Investigation on the Temperature-dependent Optical Properties of Hybrid Halide Perovskites

      Alharbi, Ohoud K. (2022-08-30) [Thesis]
      Advisor: Schwingenschlögl, Udo
      Committee members: Laquai, Frédéric; Lanza, Mario
      Nowadays, studying materials for renewable energy applications are highly de- manded. Hybrid halide perovskites have proven to be promising materials for such technology since their first application in solar cells in 2008, with a power conversion efficiency of 2.7%. Since then, hybrid halide perovskites have proven their superior properties for light-absorbing devices. In this scope, studying the optical properties is ultimately essential. This work investigates the tempera- ture dependence of the optical spectra for formamidinium lead iodide/bromide perovskites (FAPb[IxBr1-x]3 (0 ≤ x ≤ 1) using spectroscopic ellipsometry mea- surements, empirical optical modeling, density functional theory, and molecular dynamics. Five FAPb[IxBr1-x]3 perovskite samples were fabricated by a hybrid processing technique. External Quantum Efficiency measurements reported an energy bandgap range between 1.58 eV and 1.77 eV for the resulted samples. Next, multi-angle spectroscopic ellipsometry measurements were applied with a temperature-controlled stage, allowing the variance of temperature from 25 ◦C to 75 ◦C. The results show a blue shift in the optical spectra at elevated tempera- tures. We then conducted a temperature-dependent empirical model that predicts the optical spectra for the sample of study at higher temperatures using input data of the spectra at room temperature. The model reports low mean squared errors which are less than ≈ 2 around the bandgap, and further development can be applied for better utilization. First-principles investigations were conducted on four FAPb[IxBr1-x]3 per- ovskite unit cells. Structural optimization was applied with assuming fixed angles of the lattice. Atomic configuration was chosen to achieve minimal ground state energies. Ab initio molecular dynamics simulations were applied to each opti- mized structures at target temperatures of 300 K and 350 K using Berendsen thermostat. The simulation time was 4ps with 1fs time step, and the electronic energy bandgap was calculated at each step using PBE functional. The simula- tions reported a rotational motion for the FA molecule that showed to be faster at 350 K, along with higher mean energy bandgap compared to the reported value at 300 K. The optical spectra were extracted using a snapshot from the resulted structures. Similar to the spectroscopic ellipsometry measurements, a temperature induced blue shift was reported. Overall, this work detects and predicts the temperature-dependent optical spectra and confirms the role of the atomic thermal motion. With further devel- opment, higher accuracy can be achieved along with broadening the materials of study for photovoltaic and optoelectronic applications.
    • Joint Weibull Models for Survival and Longitudinal Data with Dynamic Predictions

      Uvasheva, Dilyara (2022-08-22) [Thesis]
      Advisor: Rue, Haavard
      Committee members: Moraga, Paula; Gomez-Cabrero, David
      Patients who were previously diagnosed with prostate cancer usually undergo a routine clinical monitoring that involves measuring the Prostate-specific antigen (PSA). The trajectory of this biomarker over time serves as an indication of cancer recurrence. If the PSA value begins to increase, the cancer is said to be more likely to recur and thus, the patient is advised to start a treatment. There are two reasons for stopping the patient follow-up and this poses a certain challenge. One of them is starting a salvage hormone therapy and another is actual recurrence of cancer. When analyzing such data, we need to account for informative dropout, otherwise, neglecting it may lead to increased bias in estimation of the PSA trajectory. Thus, hormone therapy serves as a censoring event, which is a defining feature of survival analysis. Motivated by the PSA data, we need to efficiently describe the dropout mechanism using the joint model. The survival submodel is based on the Weibull distribution and we use the Bayesian inference to fit this model, more specifically, we use the R-INLA package, which is a much faster alternative to MCMC-based inference. The fact that our joint model with a linear bivariate Gaussian association structure is a latent Gaussian model (LGM) allows us to use this inferential tool. Based on this work, we are then able to develop dynamic predictions of prostate cancer recurrence. Making accurate prognosis for cancer data is clinically impactful and could ultimately contribute to the development of precision medicine.
    • Characterizing the role of the BIRD proteins in Solanum lycopersicum L.

      Farran, Ayman (2022-08-17) [Thesis]
      Advisor: Blilou, Ikram
      Committee members: Merzaban, Jasmeen; Rayapuram, Naganand
      The BIRD protein JACKDAW (JKD) belong to the INDETERMINATE DOMAIN (IDD) protein family shown to regulate many developmental processes in plants. JKD encodes a Zinc Finger Protein expressed in the root ground tissue and regulates root patterning in Arabidopsis thaliana (Arabidopsis). Recent and unpublished study indicates that JKD is involved in plant defense response in Arabidopsis. Here we study the JKD function in tomato plants (Solanum lycopersicum). We analyzed the tomato JKD orthologues (Solyc09g007550 (Solyc09) and Solyc10g084180 (Solyc10)) mutant lines, which were generated by Crispr-Cas and TILLING (Targeting Induced Local Lesions in Genomes). Our data indicate that, like in Arabidopsis, Solyc09 controls root ground tissue patterning; the mutant lines show extra cell division in the inner cortex and disturbed stem cell patterning. In addition, we found that both Solyc09 and Solyc10 control the root and stem thickness and regulate tomato leaf shape. To further investigate whether Solyc09 and Solyc10 have a function in tomato when subjected to biotic stress, we evaluated the mutants response to the necrotrophic fungi Botrytis cinerea. We found that the tomato bird mutants have less infection when compared to the control. Taken together our data show that Solyc09 and Solyc10 genes play an essential role in tomato root, shoot development, and in plant immune response to the pathogenic fungi.
    • Octane Numbers And Laminar Flame Speed Predictions Using Deep Neural Networks To Enable Fuel Design For Ultra-lean Burn Engines

      Alshammasi, Rania (2022-08-15) [Thesis]
      Advisor: Sarathy, Mani
      Committee members: Castaño, Pedro; Farooq, Aamir
      High-efficiency engines have been studied to reduce the emission of CO2 in passenger cars, since they account for 41% of the transportation sector emission worldwide. Several engines have been developed, such as engine downsizing and lean burn engines, to help design fuel efficient vehicles. However, these engines require superior fuels, and the current simulations and tests used to create these types of fuels involve comprehensive chemical modeling, which must be built in individually for each fuel component and cannot be generalized. This study uses deep learning models to create a generalized approach to predict the research and motor octane numbers (RON and MON) of pure hydrocarbons along with the laminar flame speed. Three artificial neural networks and one recurrent neural network models were created to predict the octane numbers using molecular SMILES as the input parameters. Morgan Fingerprint and Mordred Descriptors were used to normalize the SMILES before using them as input parameters to train the models. The model's predictions were plotted against the actual data points used to train the models to measure the model's fittings, along with the losses to measure the model performance. The RNN model that uses Fingerprints shows the most promising results in predicting the octane numbers, and the ANN model that uses Descriptors was used to predict the laminar flame speed, and shows promising results.
    • De novo assembly of the Tamarindus indica genome as part of the Kingdom of Saudi Arabia Native Genome Project

      Navarrete Rodriguez, Maria Eugenia (2022-08-10) [Thesis]
      Advisor: Wing, Rod Anthony
      Committee members: Blilou, Ikram; Merzaban, Jasmeen
      The Kingdom of Saudi Arabia Native Genome project aims to generate genomic resources for all the plants, animals, and associated microbiome species in the Kingdom. Tamarindus indica was pointed out by the MEWA as an endangered native species in the KSA and forms part of the first 15 plant species to be studied in the NGP. A voucher tree was identified in the Rijal Almaa region, from which leaf samples were collected. HMW DNA was extracted from this tissue and sequenced using CCS with the Pac-Bio Sequel II platform. The raw data obtained from the sequencing was assembled using HIFIASM, contaminant contigs were removed, and the 15 largest contigs were selected as the primary T. indica assembly. The genome sequence of Sindora glabra was used as reference guide for primary scaffolding, and T. indica optical maps were used for super-scaffolding. Secondary scaffolding utilized Hi-C data to produce a chromosome level assembly of the T. indica genome. Transposable element analysis and a preliminary annotation were performed on the final assembly. This project represents the first step in studying T. indica for the NGP. The final assembly can be used as a foundation for more genetic studies on this species, as a possible reference for other legume species from the Detarioideae family, and for Neo-domestication and reforestation. The pipeline developed for this project can also be used as a template for sequencing and assembling the remaining species in the NGP.
    • Effect of Gallium and Platinum distribution encapsulated in Silicalite-1 (MFI) zeolite on controlled propane dehydrogenation reaction

      Almukhtar, Fadhil (2022-08-04) [Thesis]
      Advisor: Ruiz-Martinez, Javier
      Committee members: Huang, Kuo-Wei; Grande, Carlos A.
      The preparation method of the catalyst highly impacts its properties and activity. Optimizing the synthesis conditions mainly targets improving the catalyst performance and overcoming the bottlenecks such as sintering of metal active sites, deactivation, short catalyst lifetime and poor selectivity. In this study, we investigated the influence of the design and preparation method of Silicalite-1 bearing Pt and Ga active species on the properties and the performance of the catalysts for propane dehydrogenation reaction aiming to increase propylene yield. Various synthesis routes, leading to different Pt and Ga location and distances were tested: (1) supporting metals on the zeolite where both Pt and Ga are randomly distributed on the surface, (2) confining of Pt and Ga within the zeolite pores following in-situ approach with no control of their relative positions, and (3) core-shell design where one metal is confined within Silicalite-1 is covered by a Silicalite-1 layer including the second metal. The influence of structure, textural properties, location of Pt and Ga nanoparticles and their synergetic interaction to form Pt-Ga alloys were studied using several characterization techniques such as XRD, BET, TEM-EDX and NMR. Catalytic performance revealed that confining metals improved the selectivity and lifetime of the catalyst. Moreover, spatial separation of Pt and Ga through the core-shell design further boosted the reaction yield with conversions hitting the equilibrium limit. Ga/Pt ratio played a crucial role in tuning the catalyst performance. 0.26%Pt(core)-2.65%Ga(shell)@S-1 catalyst with Ga/Pt of 10 exhibited superior results of 70.5% conversion and 98% selectivity.
    • Precise genomic deletions and insertions via paired prime editing for crop bioengineering

      Moreno-Ramírez, Jose Luis (2022-08) [Thesis]
      Advisor: Mahfouz, Magdy M.
      Committee members: Blilou, Ikram; Lauersen, Kyle J.
      CRISPR/Cas has been developed for targeted mutagenesis in diverse species, including plants. However, precise genome editing via homology-directed repair (HDR) is inefficient in plants, limiting our ability to make large deletions or insertions in the plant genomes. Prime editing increases the control over the desired editing and allows the precise introduction of all types of mutations, including insertion, deletions, and all possible base conversions, albeit at low efficiencies. Here, we designed a dual prime editing system to generate large deletions and precise insertions of sequences by repairing template complementarity. We coupled dual pegRNA with Cas9 nickase (nCas9) to generate deletions and insertions. In another modality, we used dual pegRNA with wild-type Cas9 to generate double-stranded breaks to improve the editing at the targeted sites. We tested dual pegRNAs to delete the last exon in OsCCD7, delete the microRNA targeted sequence in OsIPA, and insert the T7 promoter in the 3'UTR of OsALS. Our results showed a high frequency of targeted insertion of the T7 promoter sequence in the 3'UTR of OsALS with wtCas9 and nCas9. Sanger sequencing analysis showed partial deletions at the targeted locus. Further improvements in the designs of pegRNAs will increase the precise genome insertions and deletions in plants.
    • The Influence of Varying Si/Al Ratio (SAR) of Beta Zeolite in the Methanol to Hydrocarbons (MTH) Reaction

      Bokhari, Maram (2022-08) [Thesis]
      Advisor: Ruiz-Martinez, Javier
      Committee members: Grande, Carlos A.; Khashab, Niveen M.
      Excessive greenhouse gas emissions, like carbon dioxide, contribute to global warming and climate change. Methanol is hydrogenated from syngas and can react to produce hydrocarbons in a reaction known as methanol to hydrocarbons (MTH). Catalysts are vital in this reaction and are largely of zeolite origin. The zeolite typology, acidity, and reaction conditions donate the products produced and catalytic stability. Further, previous work shows increased catalytic stability and higher desired product selectivity when metal is incorporated onto the zeolite’s framework. We study the role of varying silica/alumina ratio (SAR) of beta zeolite via dealumination and incorporating titanium to understand their effect on product distribution, catalytic lifetime, and deactivation in the MTH reaction The samples maintained their structural integrity following the dealumination and metal incorporation. Techniques like XRD, N2 physisorption, ICP–OES, FTIR, and Raman spectroscopy are shown and discussed. They confirm the preservation of the zeolite structure following dealumination and metal incorporation. Pyridine-FTIR and ammonia TPD are used to understand the acidity character of the samples. Both show decreased acidity as the SAR increases. 27Al NMR and 1H NMR show the removal of extra framework 27Al as SAR increases and the presence of silanol nests in the dealuminated samples, respectively. A packed bed reactor in a PID setup with a UV-vis probe is used to test the catalytic activity and study the neutral and charged species formation, respectively. The catalytic activity results show a decrease in conversion as the SAR increases for the dealuminated samples. High propylene/ethylene ratio reaching up to 41.5 is observed for the 13M sample. Further, the UV-vis analysis shows the higher formation of bulkier hydrocarbons, like polyaromatics, as the reaction progresses. It is found that the parent sample deactivates quicker than the dealuminated samples as it presents stagnant UV-vis bands at the end of the reaction. The higher accumulation of polyaromatics and lower product formation of ethylene, in higher SARs, is related to the aromatic cycle hindrance and the dominance of the olefinic cycle products.
    • Dry Reforming of Methane by Ni-In-Ce Supported Catalysts

      Alharbi, Abdulrahman (2022-08) [Thesis]
      Advisor: Ruiz-Martinez, Javier
      Committee members: Grande, Carlos A.; Huang, Kuo-Wei
      In light of global warming’s environmental implications, research is shifted towards potential processes that can utilize CO2 and reduce its emissions in the industrial sector. One of the promising processes is dry reforming of methane (DRM), which is capable of utilizing CO2 and producing valuable syngas (H2 and CO). The main challenge of DRM is the deactivation of catalysts under the reaction temperatures (above 700 °C) due to sintering of the active metal and coke formation. Ni-based catalysts are the most widely investigated catalysts in literature for DRM due to their cost efficiency and availability. This study is an extension of the work done by Saudi Basic Industries Corporation (SABIC) devoted to investigating Ni-Ce-In system for DRM reaction. Five catalysts were synthesized by dry impregnation method according to SABIC synthesis procedure (Ni/Al2O3, Ni-In/Al2O3, Ni/CeO2/Al2O3, Ni/In-CeO2/Al2O3, and Ni-In/CeO2/Al2O3). The metallic loading targets were 7.5 wt.%, 10 wt.%, and 0.8 wt.% for nickel, cerium, and indium, respectively. The addition of indium in combination with cerium resulted in the highest catalytic activity. Additionally, the co-impregnation of indium and cerium resulted in enhancing the catalytic activity more than subsequential impregnation (Ni/In-CeO2/Al2O3 compared to Ni-In/CeO2/Al2O3). The addition of cerium or indium separately with nickel did not seem to affect activity since Ni/Al2O3, Ni-In/Al2O3, and Ni/CeO2/Al2O3 exhibited similar conversion values. All catalysts were stable for more than two days under DRM conditions without deactivating. Therefore, deactivation behaviors of the catalysts were not covered in this study.
    • Influence of A-site Cation Composition on Electronic Properties of Halide Tin Perovskites

      Tounesi, Roba S. (2022-08) [Thesis]
      Advisor: Baran, Derya
      Committee members: Bakr, Osman; Heeney, Martin
      Tin halide perovskites are gaining interest as a replacement for lead perovskites for various device applications. However, compared to lead-based perovskites, the understanding of their charge transport properties has received limited attention. In particular, the effect of A-site cation on electronic properties of tin perovskites warrants further attention to design efficient material systems for various applications beyond photovoltaics. In the presented work, leveraging the composition tunability of halide perovskites, we establish a relationship between the A-site composition and electronic properties in tin perovskites (ASnI3). The effect of prototypical A-site cations such as Formamidinium (FA), Methylammonium (MA), Cesium (Cs), and their binary combinations on structure, morphology, and electronic properties are explored. MACs combination offers the highest electrical conductivity owing to enhanced mobility compared to mono-cations MA and Cs, resulting in an impressive electrical conductivity of ∼ 143 Scm−1 and thermoelectric power factor of ∼ 149 μW m−1K−2. The library of properties generated for Sn perovskites in this work will be helpful for their further development as an electronic material.
    • Xeno-pumice from Harrat Rahat: Understanding magma-crust interaction

      Garcia, Evelyn R. Garcia Paredes (2022-07-28) [Thesis]
      Advisor: Van der Zwan, Froukje M.
      Committee members: Jonsson, Sigurjon; Troll, Valentin R; van Buchem, Frans
      “Xeno-pumice” describes a pumice-like material, high in silica content and vesiculation, found as a xenolith in a more mafic rock. A xeno-pumice is an indicator of magma-crust interaction; however, the origin, nature, and processes behind this xenolith are still debated. Xeno-pumice has been described in a few places worldwide, including the Canary Islands in Spain, Indonesia, Iceland, the USA, Chile and Mexico. This thesis, for the first time, presents and analyzes the mineralogy, textural features, whole-rock geochemistry (major and trace element), and oxygen isotopes of xeno-pumice samples found in Harrat Rahat, Saudi Arabia. Harrat Rahat is a volcanic field whose last eruption was in 1256A.D. and reached the outskirts of Madinah, one of the main cities in Saudi Arabia. Harrat Rahat is characterized by a wide range of volcanic products: from basalts to trachyte. Previous studies suggested that this chemical variation has its source in the mantle and minor crustal contamination; however, the xeno-pumice samples found indicate magma-crust interaction. Thus, in this thesis, the crust-melt interaction hypothesis is addressed as a process that could modify the composition of the melt and thus the resulting volcanic products and eruptive style of the volcanic field. Indeed, the chemistry and oxygen isotope values of the studied volcanic rocks show a variation in composition, which is suggested to be the consequence of crust-melt interaction. The petrology, chemistry and oxygen isotope values suggest that the melt interacted with either the metamorphosed plutonic portion of the upper Arabian crust or with (meta-) sediments below Harrat Rahat. Finally, this thesis proved that magma-crust interaction occurred at Harrat Rahat, which has important implications for interpreting eruption mechanisms and mantle sources.
    • Establishment of 3D culture protocols for the maintenance and expansion of human pluripotent stem cell aggregates in a low scale platform and in the DASbox® Mini-Bioreactor System

      Hernandez-Bautista, Carlos Alberto (2022-07-27) [Thesis]
      Advisor: Adamo, Antonio
      Committee members: Merzaban, Jasmeen; Ibrahim, Leena Ali
      The human Embryonic Stem Cells (hESCs) and human induced Pluripotent Stem Cells (hiPSCs) have offered numerous advantages including but not limited to model diseases, high-throughput drug screening, and regenerative purposes. However, the employment of monolayer cultures has not been sufficient to mimic the in vivo stem cells niche. Thus, three-dimensional suspension cultures have helped us to advance our knowledge and ease the development of the human organs’ counterparts, commonly referred as organoids. Currently, the challenge is the generation of homogenous and reproducible human Pluripotent Stem Cell (hPSC) aggregates, the basic cellular unit to derive organoids. To date, the Ultra-Low Attachment (ULA) 6-well plates have been routinary used for the hPSC aggregates formation, which mainly relies on the inhibition of the Rho-associated kinase (ROCK) pathway resulting in the enhancement of cell survival coming from cryopreserved stocks or when passaging. However, little is known in this regard when analyzing the aggregate formation of hPSCs with two widely used compounds: RevitaCellTM Supplement and Y27632. Importantly, due to the high demand required from the regenerative medicine, I aimed to upscale the hPSC aggregates production in the DASbox® Mini-Bioreactor System. In this thesis, I established protocols for the hPSC aggregates formation by using two different types of media in two platforms being the ULA 6-well plates and the DASbox® Mini-Bioreactor System. In addition, I demonstrated that monolayer confluence cultures before single cell inoculations are paramount for the formation of bona fide hPSC aggregates in healthy and X aneuploid hiPSCs, precisely two hESCs and five hiPSCs.
    • Evaluative screening of kinetic models for simulating the performances of oxidative coupling of methane catalysts

      Gobouri, Abdullah (2022-07-27) [Thesis]
      Advisor: Castaño, Pedro
      Committee members: Ruiz-Martinez, Javier; Hauser, Charlotte
      In this work, multiple kinetic models have been screened as potential candidates for simulating the performances of three oxidative coupling of methane (OCM) catalysts. Two of the proposed models were subjected to testing and optimization. The types of models screened covered both kinetic and microkinetic type models, i.e., radical omitting and radical considering. Some of the models only accounted for catalytic heterogeneous pathways, while others have expanded on the homogeneous gas-phase mechanism of the OCM reaction. The optimization process was carried out in MATLAB® R2020a using an error minimization tool. The range of experimental conditions examined was as follows: 740–800◦C, 100 kPa, 2–4 CH4/O2 ratio, 1–6 gcat h molC –1 spacetime. The results show successful optimization of both models as well as discrepancies in terms of their performances in predicting experimentally obtained values of CH4 and O2 conversions, as well as selectivities towards COx and C2+ products. While a kinetic model served as an easy option to optimize, it expressed limits in terms of achievable performance, mainly failing to simulate experimental runs conducted at low spacetimes. A microkinetic model on the other hand, managed to simulate all experimental conditions, with less accuracy towards COx species and much greater computational demand.
    • Sars-Cov-2 Intra-Host Evolution in Immunocompromised Patients for the Emergence of Variants of Concerns, Including Omicron.

      Bantan, Azari I. (2022-07-21) [Thesis]
      Advisor: Gojobori, Takashi
      Committee members: Mineta, Katsuhiko; Pain, Arnab
      Unexpected high mutations detected in new emerging variants of concern (VOCs) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), especially in the case of omicron, raises concerns and efforts to understand their evolutionary trajectory. Several hypotheses have been discussed in literature to conceptualize the source of their emergence, including intra-host viral evolution in immunocompromised patients. These patients grant opportunities for the emergence of new variants through a persisting virus winning against host immunity, and selection for viral mutations driven by treatment interventions. VOCs have in common high mutation rate exceeding the average rate of 1-2 mutations per month. Not many studies have investigated the evolutionary rate of SARS-CoV-2 in immunocompromised candidates. Therefore, the purpose of this study is to reveal potential mechanisms underlying the emergence of VOCs by exploring substitution rate of SARS-CoV-2 genomes from surveyed COVID-19 immunocompromised patient’s studies. First, SARS-CoV-2 genome sequences were collected at sequential time series throughout host infection, which were reported in the previous studies. Filtration criteria was applied to reanalyze patients with prolonged infection documented for ≥ 2 months, and comprehensive sequenced samples for ≥ 6 time points. Then, phylogenetic analysis was conducted using Nextclade (, followed by mutation rate analysis using two substantial similar approaches to calculate the rate in i) substitutions per month and ii) substitutions per site (per year). The mutation tendency of SARS-CoV-2 in immunocompromised hosts was compared to reported VOCs, particularly to omicron. The highest observed mutation rate accounted for approximately 2.2 mutations per month, which is higher than the average rate. High mutation rate was due to prolonged infection and selection pressure by treatment interventions (i.e., convalescent plasma and antibodies). Here, higher rate of intra-host viral evolution in immunocompromised patients is detected, potentially leading to the emergence of VOC. Hence, this research highlights the need for sequencing efforts in high-risk individuals, updating treatment strategies along with further analysis on adaptive mutants pronounced due to intra-host evolution. Together, such findings provide an ultimate synergy for future public health guidelines and infection control measures.
    • De novo genome-scale prediction of protein-protein interaction networks using ontology-based background knowledge

      Niu, Kexin (2022-07-18) [Thesis]
      Advisor: Hoehndorf, Robert
      Committee members: Inal, Sahika; Moshkov, Mikhail
      Proteins and their function play one of the most essential roles in various biological processes. The study of PPI is of considerable importance. PPI network data are of great scientific value, however, they are incomplete and experimental identification is time and money consuming. Available computational methods perform well on model organisms’ PPI prediction but perform poorly for a novel organism. Due to the incompleteness of interaction data, it is challenging to train a model for a novel organism. Also, millions to billions of interactions need to be verified which is extremely compute-intensive. We aim to improve the performance of predicting whether a pair of proteins will interact, with only two sequences as input. And also efficiently predict a PPI network with a proteome of sequences as input. We hypothesize that information about cellular locations where proteins are active and proteins' 3D structures can help us to significantly improve predict performance. To overcome the lack of experimental data, we use predicted structures by AlphaFold2 and cellular locations by DeepGoPlus. We believe that proteins belonging to disjoint biological components have very little chance to interact. We manually choose several disjoint pairs and further confirmed it by experimental PPI. We generate new no-interaction pairs with disjoint classes to update the D-SCRIPT dataset. As result, the AUPR has improved by 10% compared to the D-SCRIPT dataset. Besides, we pre-filter the negatives instead of enumerating all the potential PPI for de-novo PPI network prediction. For E.coli, we can pass around a million negative interactions. To combine the structure and sequence information, we generate a graph for each protein. A graph convolution network using Self-Attention Graph Pooling in Siamese architecture is used to learn these graphs for PPI prediction. In this way, we can improve around 20% in AUPR compared to our baseline model D-SCRIPT.
    • Water Effect on the Methanol to Olefin Conversion over SSZ-13 Catalyst with an Operando Spectroscopy

      Alsindi, Mohammed (2022-07-18) [Thesis]
      Advisor: Ruiz-Martinez, Javier
      Committee members: Pinnau, Ingo; gomez-cabrero, David
      For more than 50 years, the methanol to olefins (MTO) reaction remains to be a hot topic within the catalysis community. The recent discoveries about it and the industrial implementation made it even receive more attention. The best way this process can be used is by hydrogenation of CO2 to make methanol and undergo after that the MTO reaction. This method will save energy, be more environmentally friendly, and be sustainable, but it requires advancement regarding carbon capture. The purpose of this paper is to understand the effect of water on SSZ-13 commercial zeolite when it is used for MTO reaction by a combination of gas chromatography (GC) analysis and operando UV – vis spectroscopy. It was observed that water with a ratio of 2:1 methanol to water would increase the lifetime of the catalyst from 3 h to 6.5 h, and the ratio of 1:1 would increase it to 9 h. However, a higher amount of water hadn’t been analyzed, but theoretically, it would cause dealumination to the zeolite invoking a different type of deactivation. This increase in catalyst lifetime was first due to the competitive adsorption between water and methanol; leading to a lower methanol reactivity toward methoxide formation. Second, because of the competition between water and propylene, it resulted in a longer induction period and a delay in the formation of hydrocarbon pool. Hence, less coke was formed from the reaction and more species were able to diffuse into the inner pores. Also, it was observed that ethylene selectivity increased with the addition of water to the feed. The UV-vis analysis proved the longer induction period and showed the formation of more species due to that. The deactivating materials were identified to be polyaromatic carbocation and phenanthrene, while the main activating species was methylated naphthalene carbocation. In addition, multiple characterization techniques, such as nitrogen physisorption, ammonia TPD, and SEM, were performed to understand the nature of the catalyst. It was found that it has weak and strong Bronsted acid sites, BET surface area of 665.7 m2/g, and crystal size of about 0.5 – 2 µm.
    • Benthic Habitat Mapping of Thuwal’s Reefs Using High-Resolution Acoustic Technologies and Imaging Data

      Watts, Marta A. Ezeta (2022-07-14) [Thesis]
      Advisor: Benzoni, Francesca
      Committee members: Berumen, Michael L.; Volker, Vahrenkamp
      Remote sensing studies based on satellite and aerial imagery have improved our understanding of the morphology and distribution of several shallow reefs along the Red Sea Arabian coast and of the benthic assemblages associated to them (Bruckner et al., 2011; Bruckner et al., 2012; Rowlands et al., 2016). However, data concerning the deeper benthic assemblages' composition and spatial distribution in the central Red Sea are still missing. Using high-resolution acoustic technology and an underwater remotely operated vehicle (ROV), we aim to map, describe, and classify the reefs found in Thuwal's coastal area, filling the information gap by producing the first benthic habitat map of this area and making progress towards the evaluation of shallow and upper mesophotic benthic resources in the Saudi Arabian Red Sea. High-resolution acoustic data was collected using a multibeam echosounder system, which generated a bathymetric model. Based on this, the seafloor features were classified into 12 morphotypes following a visual assessment. Based on the morphotypes classification, 28 sites were visually selected for ground-truthing data acquisition and characterization of the substrate and benthic assemblages using a remotely operated vehicle equipped with an ultra-short baseline (USBL) positioning system. With the information obtained from the bathymetry data and the ROV video transects, a Top-Down approach in which we analyzed, categorized, and classified the data was used to create Thuwal's reefs benthic habitat map in which 23 different benthic habitat types were identified. This research uncovered previously poorly studied reef morphologies in the Red Sea and their associated benthic assemblages. Moreover, this work will help improve the understanding of the spatial distribution of benthic communities located on Thuwal's reefs, giving a baseline with the potential to provide fundamental information that can be used for mapping, management, conservation, and future research at other Red Sea reef sites in Saudi Arabia.
    • Fast, Robust, Iterative Riemann Solvers for the Shallow Water and Euler Equations

      Muñoz-Moncayo, Carlos (2022-07-12) [Thesis]
      Advisor: Ketcheson, David I.
      Committee members: Tzavaras, Athanasios; Truscott, T. T.
      Riemann problems are of prime importance in computational fluid dynamics simulations using finite elements or finite volumes discretizations. In some applications, billions of Riemann problems might need to be solved in a single simulation, therefore it is important to have reliable and computationally efficient algorithms to do so. Given the nonlinearity of the flux function in most systems considered in practice, to obtain an exact solution for the Riemann problem explicitly is often not possible, and iterative solvers are required. However, because of issues found with existing iterative solvers like lack of convergence and high computational cost, their use is avoided and approximate solvers are preferred. In this thesis work, motivated by the advances in computer hardware and algorithms in the last years, we revisit the possibility of using iterative solvers to compute the exact solution for Riemann problems. In particular, we focus on the development, implementation, and performance comparison of iterative Riemann solvers for the shallow water and Euler equations. In a one-dimensional homogeneous framework for these systems, we consider several initial guesses and iterative methods for the computation of the Riemann solution. We find that efficient and reliable iterative solvers can be obtained by using recent estimates on the Riemann solution to modify and combine well-known methods. Finally, we consider the application of these solvers in finite volume simulations using the wave propagation algorithms implemented in Clawpack.
    • Estimation of Mercury Injection Capillary Pressure (MICP) from the Nuclear Magnetic Resonance (NMR) exponential decay with the Machine Learning (ML) Neural Network (NN) approach

      Ugolkov, Evgeny A. (2022-07-09) [Thesis]
      Advisor: Hoteit, Hussein
      Committee members: Santamarina, Carlos; Ahmed, Shehab
      Information about the capillary pressure has a wide range of applications in the petroleum industry, such as an estimation of irreducible water saturation, calculation of formation absolute permeability, determination of hydrocarbon-water contact and the thickness of the transition zone, evaluation of the seal capacity, and an estimation of relative permeability. All the listed parameters in the combination with petrophysical features, pressures, and fluid properties allow us to evaluate the economic viability of the well or the field overall. For this reason, capillary pressure curves are of great importance for petroleum engineers working on any stage of the field development: starting from exploration and finishing with production stages. Nowadays, capillary pressure experiments are provided either in the lab on the plugs of the rocks, either in the well on the certain stop points with the formation tester tools on the wire or tubes. Core extraction and formation testing are both laborious, expensive, and complicated processes since the newly-drilled well remain in the risky uncased condition during these operations, and for this reason, usually the listed works are provided in the exploration wells only. Afterward, the properties obtained from the exploration wells are assumed to be the same for the extraction or any other kinds of wells. Therefore, these days petroleum engineers have limited access to the capillary pressure curves: the modern tests are provided on the limited points of formation in the limited number of wells. An extension of capillary pressure measurements in the continuous mode for every well will dramatically expand the abilities of modern formation evaluation and significantly improve the field operation management by reducing the degree of uncertainty in the decision-making processes. This work is the first step toward continuous capillary pressure evaluation. Here we describe the procedure of finding the correlation between the results of the lab Nuclear Magnetic Resonance (NMR) experiment and lab Mercury Injection Capillary Pressure (MICP) measurements. Both experiments were provided on the 9 core plugs of the sandstone. Afterward, a Machine Learning (ML) algorithm was applied to generate additional samples of the porous media with different petrophysical properties representing the variations of the real cores of available sandstones. Overall, 405 additional digital rock models were generated. Thereafter, the digital simulations of MICP and NMR experiments were provided on the generated database of digital rocks. All the simulations were corrected for limited resolution of the CT scan. Based on the created database of experiments, we implemented a ML algorithm that found a correlation between the NMR echo data and MICP capillary pressure curves. Obtained correlation allows to calculate capillary pressure curve from the NMR echo data. Since NMR logging may be implemented in every well in the continuous mode, an extension of the created technique provides an opportunity for continuous estimation of capillary pressure for the whole logging interval. This extension is planned as future work.