• Cycloalkane Metathesis using a Bi-metallic System: Understanding the Effect of Second metal in Metathesis Reaction

      Alshanqiti, Ahmed M. (2018-09)
      Over the past decades, since the discovery of a single–site silica-supported catalyst for the alkane metathesis reaction by our group, we have been extensively working on the development of supported catalytic systems for the improved alkane metathesis reaction. During these developments, we understand the reaction mechanism and reached a new perspective for the synthesis of various supported bimetallic systems via the surface organometallic chemistry (SOMC) approach. Recently, with this bi-metallic system, we got a very high TON (10000) in propane metathesis reaction. As these catalysts are very efficient for linear alkanes we thought to apply it for cyclo-alkanes specifically, for cyclo-octane metathesis expecting better activity. Besides, the value of the ring alkanes are higher than the linear alkanes. The current work demonstrates a combination of [(ΞSi−O−)W(Me)5] and [(ΞSi− O−)Ti(Np)3 pre-catalyst with several supports (SiO2-700, SBA-15 and MCM-41) for metathesis of cyclooctane. The catalysts have been synthesized and fully characterized by elemental analysis (EA), FT-IR and NMR spectroscopies. After fully characterization the bi-metallic catalyst was tested for metathesis of cyclooctane with highest ever TON 2500 as compared to that of mono-metallic catalyst where we got 430 TON. Which again corroborates our prediction that bimetallic catalysts are better catalysts than monometallic catalysts.
    • Biological and Biochemical Properties of Two KDM1A Associated Alternatively Spliced SWIRM Domains

      Fadaili, Yara (2018-11)
      LSD1 is the first described histone demethylase which demethylates H3K4me1/2 (Shi et el., 2004), thus, causing transcriptional repression. Alternatively, LSD1 was demonstrated to have H3K9me1/2 demethylase activity when bound by androgen receptor, hence, causing transcriptional activation (Schule et al., 2005). LSD1 is commonly recruited by the so called CoREST core complex including: RCOR1, HDAC1 and HDAC2 among others and therefore is coupled with histone deacetylation and transcriptional repression (Foster et al., 2010). It is an important regulator of pluripotency in early development and it occupies, along with pluripotency factors NANOG and OCT4, the promoters of major lineage determining genes that are poised for activation in the pluripotent state, (Adamo et al., 2011). There are four described isoforms for LSD1: LSD1, LSD1-E2a, LSD1-8a and LSD1-E2a/E8a (Zibetti et al., 2010). While the Cterminus of LSD1 is extensively studied and the function of the isoforms LSD1-E8a and LSD1-E8aE2a is described, there is scarce knowledge on LSD1 N-terminus unstructured region and the SWIRM domain. In this project I examined the role of the differently spliced exon 2a on the function of the SWIRM domain through generation of eight constructs coding for the N-terminal portion of LSD1 SV1 and SV2 fused with a C- or N-terminus FLAG tag. I then performed an immunoprecipitation experiment followed by mass spectrometry and proteomics analysis that led to the identification of previously unknown binding partners to the LSD1 SWIRM domain: NONO and IGF2B3.
    • The Effect of Increasing Temperature on Greenhouse Gas Emissions by Halophila stipulacea in the Red Sea

      Burkholz, Celina (2018-12)
      Seagrass ecosystems are intense carbon sinks, but they can also emit greenhouse gases (GHG), such as carbon dioxide (CO2) and methane (CH4), to the atmosphere. Yet, GHG emissions by seagrasses are not considered when estimating global CH4 production rates by natural sources, although these estimations will help predict future scenarios and potential changes in CH4 emissions. In addition, the effect of warming on GHG emissions by seagrasses has not yet been reported. The present study aims to assess the CO2 and CH4 production rates by vegetated and adjacent bare sediment of a monospecific seagrass meadow (Halophila stipulacea) located in the central Red Sea. We measured CH4 and CO2 fluxes and their isotopic signatures by cavity ringdown spectroscopy on chambers containing vegetated and bare sediment. The fluxes were measured at temperatures from 25 °C (winter seawater temperature) to 37 °C to cover the natural thermal range and future seawater temperatures in the Red Sea. Additional parameters analyzed included changes in the sediment microbial community composition, sediment organic matter, organic carbon, nitrogen, and phosphorus concentration. We detected up to 100-fold higher CH4 (up tp 571.65 µmol CH4 m−2 d−1) and up to six-fold higher CO2 (up to 13,930.18 µmol CO2 m−2 d−1) fluxes in vegetated sediment compared to bare sediment, and an increase in CH4 and CO2 production with increasing temperature. In contrast, CH4 and CO2 production rates decreased in communities that were maintained at 25 °C, while communities that were exposed to prolonged darkness showed a decrease in CH4 and an increase in CO2 production rates. However, only minor changes were seen in the microbial community composition with increasing temperatures. These results show that GHG emissions by seagrasses might be affected by natural temperature extremes and warming due to climate change in the Red Sea. The findings will have critical implications for the estimation of natural GHG sources, especially when predicting future changes in the global CH4 budget.
    • Sand temperature profiles at turtle nesting sites in the Red Sea: implications for hatchling sex ratios

      Tanabe, Lyndsey K. (2018-11)
      Climate change poses a serious threat to species that demonstrate temperature dependent sex determination (TDS), including marine turtles. Increased temperatures can result in highly female skewed sex ratios and decreased hatchling success. In situ sand temperature data was collected from the nesting depth of hawksbill and green turtles at five study sites along the coast of the Red Sea. The sand temperature profile at four of the sites exceeded the pivotal temperature of 29.2°C (commonly cited in literature) throughout the study duration, which suggests feminization of turtles could be occurring, but further studies need to identify the pivotal temperature in this region. The percentage of days exceeding the commonly cited maximum thermal threshold (33 and 35°C) was calculated for each site at 30 and 50 cm. Sand temperature recordings were as high as 36.0°C at 30 cm depth, and 35.3°C at 50 cm. This suggests that the turtle hatchlings in some areas of the Red Sea could already have high mortality rates due to high temperatures, unless they are locally adapted to these high temperatures. The Red Sea is home to five out of the seven extant species of marine turtles in the world, but not much is known about these populations. The Red Sea is an understudied region of the world, but it has the potential to provide insight on how species might adapt to future climate change due to its high and variable water temperatures (range of 20°C to 35°C) and high salinity (40 PSU). Sites with lower sand temperatures (and lower risk of feminization) may represent priority areas for conservation efforts, particularly in regions facing imminent coastal development.
    • Single-Copy Insertion of Split-GFP for the Restriction of Germline Expression in Caenorhabditis elegans

      Al Johani, Mohammed (2018-11)
      Gene regulation in C. elegans germ cells depend on transgenerational chromatin modification and small RNA pathways. Germline silencing mechanisms evolved to repress foreign DNA from compromising the transfer of genetic information to progeny. Effective genetic tools that circumvent the silencing machinery will facilitate studies using this model organism. Specifically, translation of heat-shock inducible transgenes is inhibited in the germline making it challenging to transiently express enzymes to modify the genome. Here, we describe a genetic screen design that can be used to identify pathways that prevent germline expression of heat-shock induced transgenes. We use split-GFP (GFP1-10 and GFP11) to confine a genetic screen to germ cells. Stable transgenic lines with germline expression of single-copy integrated GFP11 were produced using MosSCI. The insertion lines will be used in RNAi or chemical mutagenesis screens for the germline de-repression of GFP1-10 expressed under heat-shock promoters. The screen is likely to identify candidate RNAi or chromatin factors involved in repressing heat-shock expression in the germline, particularly from extrachromosomal arrays. Inducible high-level expression in the germline from extrachromosomal arrays would be a valuable tool for large-scale genome engineering.
    • How does light affect the heat stress response in Arabidopsis?

      Kim, Eunje (2018-11)
      Light and temperature are two of the most important environmental factors regulating plant development. Although heat stress has been well studied, little is known about the interaction between light and temperature. In this study, we performed phenotypic assays comparing seedling responses to heat under light and dark conditions. Seedlings exposed to heat in the dark show lower survival rates than seedlings stressed in the light. To identify transcriptional changes underlying light-dependent heat tolerance, we used RNA-sequencing. The light-dependent heat stress responses involved a plethora of genes which could be potential candidate genes for light-induced heat tolerance, including transcription factors (bHLH) and genes commonly associated with biotic stress. By using the latest high-throughput phenotyping facility, we found that the light-dependent heat tolerance is reflected more on the maintenance of photosynthetic capacity, rather than leaf temperature. These results provide insights into how light increases heat stress tolerance in Arabidopsis seedlings and suggest its underlying mechanisms.
    • Effect of Boron on Nickel and Cobalt Catalysts for the Dry Reforming of Methane

      Al Abdulghani, Abdullah (2018-11)
      The dry reforming of methane (DRM) has received critical attention because it converts two major greenhouse gases, methane and carbon dioxide, into molecular hydrogen and carbon monoxide, known as synthesis gas (syngas). Syngas is an important feedstock to produce various chemicals. A major drawback of the DRM process is the high deactivation rates of conventional nickel and cobalt catalysts. Experimental findings indicate that treating nickel and cobalt catalysts with boron reduces deactivation rates and enhances the catalytic activity. This study investigates the mechanism through which boron promotes catalytic stability using density functional theory calculations. First, the location of boron in nickel and cobalt catalysts is explored. Boron is found to be more stable occupying on-surface and substitutional sites in the catalysts. However, during DRM operation, carbon dioxide is able to oxidize on-surface and substitutional boron. The formed boron oxide units may react with each other and form diboron trioxide or react with hydrogen to form boric acid, and eventually leave the catalyst, which means they cannot have an effect on deactivation rates. This study argues that interstitial boron plays the major role since it is protected from getting oxidized by carbon dioxide. Geometric optimization indicates that interstitial boron leads to spontaneous surface reconstruction in both extended surfaces and nanoparticles. The effect of interstitial boron on the binding energies of methyl, hydrogen, carbon monoxide, and oxygen on extended surfaces and nanoparticles is studied and utilized using the Brønsted-Evans-Polanyi principle to give an insight about how boron reduces deactivation rates. Our analysis indicates that interstitial boron lowers the activation energies of methane and carbon dioxide. On (100) surfaces, boron lowers C–H activation energies in methane more than it lowers C=O activation energies in carbon dioxide, which means catalytic deactivation rates due to metal oxidation are lowered. On (111) surfaces, boron lowers carbon dioxide activation energies more than it lowers methane activation energies, which means catalytic deactivation rates due to coke formation are lowered. The computational study is consistent with experimental findings and gives an atomistic understanding of the beneficial role of boron on the DRM process catalyzed by nickel and cobalt.
    • Fine Jetting from Drops Impacting on a Superhydrophobic Surface

      Alhazmi, Mohammad A. (2018-10)
      In this study, the associated dynamic of water droplets at low impact velocity on the Superhydrophobic surface have been investigated. The experiment is conducted on superhydrophobic surface (SH), (Contact Angel > 1500) while varying the impact velocity (V0). When the drop hits the surface, large oscillation starts, and the capillary waves travel up to the upper of the drop where a cylindrical cavity can be formed inside the drop. The cavity closes up in a self-similar way until collapse, followed by a violent singular jet which can reach up to 35 m/s. The study showed that during drop receding, the cavity can collapse in different scenarios based on the impact velocity and the surface wettability. More importantly, the collapse is observed for the first time at very high-speed video, up to 5 million fps. Furthermore, we correct the optical distortion of the cavity due to the curvature of the drop surface. This study classifies all of the 5 encountered behaviors of the cavity collapse. The jet formation and speed are strongly dependent on the specific cavity configuration. Very fast jetting behavior is observed when the collapse is pinch-off singularity which reaches zero value in the middle of the drop. Other behaviors of the collapse such the unsymmetrical closing of the cavity or bubble entrapment is discussed. The optical distortion factor is calculated through 3 different approaches. The first one is an experimental calibration technique where a small cylinder is inserted into the drop. While the other two approaches are indirect implantations of theoretical models presented in the literature to fit the instantaneous geometrical shape of the cavity inside the drop. The distortion factor (DF) gives in all cases a similar value. Therefore, the averaged distortion value is calculated, and it is a magnification of 33% increase of the actual size. The experiment results of the cavity radius are compared with power-laws and the modified Rayleigh-Plesset equation for free cylindrical flow and good agreement is shown.
    • Preparation of modified DNA molecules for multi-Spectroscopy Application

      zhang, xinyu (2018-11-29)
      Hot Electron Nanoscopy and Spectroscopy (HENs) is a current-sensing AFM technique recently developed in our lab, which have proven a new kind of response on conduction at the nanometer scale, casting a new light for the comprehension of electronic states in nanomaterials. Direct imaging of DNA structure has long been investigated, with the development of HENs technology, more structural information about DNA could be revealed by simultaneous measurements of height, phase, Raman signal, and conductivity. With the aim of applying it for the first time on biological molecules, customized double-stranded DNA sequences, including thiol-modified oligonucleotides are designed to create preferential conductive paths through the basis as a benchmark system for the technique on biomolecules. This work aims to a final goal to characterize hot-electron current between gold tip and thiol modified DNA which ideally is covalently bonded to the gold surface and optimized for the application. In this work, high density of DNA absorbed by SERS active gold surface with atomic flat islands has been prepared for HENs application. The samples have been characterized by AFM, SKPM and Raman Spectroscopy, as non-destructive and controlled interactive image analysis. High-resolution images of DNA have been acquired, S-S and Au-S bonding of DNA anchored on SERS active gold substrate are also visible with Surface-enhanced Raman and Tip-enhanced Raman signals. A submolecular feature has also been found in both topographical and electrical results. Herein, we report the synthesis and characterization steps to obtain the optimized operation standard.
    • A Biocomputational Study of Water-Nucleobase Stacking Contacts in Functional RNAs

      Kalra, Kanav (2018-12)
      Recent structural studies evidenced the presence of a recurring well-known interaction between an oxygen atom and an aromatic nucleobase ring in structural motifs of nucleic acids. In particular, this type of interaction is observed between the O4' atom of the (deoxy)ribose moiety and the aromatic nucleobase in Z-DNA molecules and in a variety of structural RNA molecules. In this thesis, we comprehensively examine the hitherto undetected stacking interactions between an oxygen atom of a water (Ow) molecule and the aromatic nucleobase ring, using structural bioinformatics along with quantum mechanics. On the basis of the structural analysis of the high-resolution X-ray structures, we found out that the stacking distance between the Ow atom and the nucleobase plane varies between 3.1 and 4.0 Å. Further, the contact between the Ow-nucleobase plane can be categorized either as a lonepair-π type, where the Ow atom interacts directly with the aromatic surface of the nucleobase, or as an OH-π interaction, where one of the hydrogen atoms of the Ow points towards the nucleobase. Our quantum chemical analysis evidenced that the OH-π interaction is clearly favored in terms of energetics when compared to the lonepair-π, except for the uracil, where the lonepair-π kind of interaction seems to be energetically more stable, as also supported by electrostatic potential map calculations.
    • Modeling and Analysis of Hybrid Aerial-Terrestrial Networks: A Stochastic Geometry Approach

      Alshaikh, Khlod K. (2018-12)
      The ever-increasing demand for better mobile experiences is propelling the research communities to look ahead at how future networks can be geared up to meet such demands. It is likely that the next-generation of wireless communications will be revolutionary, outpacing the current systems capabilities in terms connectivity, reliability and intelligence. These trends and predictions will cause a revolutionary change in the wireless communications. In this context, the concept of Ultra-Dense Network (UDN) is poised to be the cornerstone of the development of fifth generation(5G) systems, whereby a massive number of base stations (BSs) are deployed for enhancing the network performance metrics. Though such densification might be economically viable in urban areas, it is mostly unfavorable in rural ones due to the sheer complexity and the various factors involved the planning and installation processes; all of which trigger the need for cost-effective, flexible and easily-implementable solutions. As a result, unmanned aerial vehicles (UAVs) emerge as a promising alternative solution for enhancing wireless coverage. Due to their mobility capabilities, UAVs are of particular importance in events of (i) terrestrial-based cellular systems dilapidation, (ii) infrastructure absence in remote and suburban areas, or (iii) limited-duration events or activities wherein there is a short-term need for supplementary network resources to handle the overload. While a growing body literature works towards characterizing and providing insights into the performance of UAVs-only networks (serving the first two purposes), understanding the performance of such networks when coupled with existing terrestrial BSs remains a challenging, yet interesting, open research venue. Towards this direction, this thesis provides a rigorous analysis of the downlink coverage probability of hybrid aerial-terrestrial networks using tools from Stochastic Geometry. The thesis presents a mathematical model that characterizes the coverage probability metric under different network environments. The proposed model is validated against intensive simulations so as to substantiate the analytical results. The developed work is essential to understanding the premises of one possible solution to the UDNs of tomorrow, capture its key performance metrics and, most importantly, to uncover key design insights and reveal new directions for the wireless communication industry.
    • Superwettable Membranes for Highly Efficient Separation of Oil-in-Water Emulsions

      Alduraiei, Fadhilah H. (2018-11)
      In this work, we report a facile and robust surface membrane modification method via a simple coating of PVDF membrane using tannic acid (TA) followed by oxidation with sodium periodate (NaIO4). The modified membranes were investigated by SEM, AFM, XPS, FTIR, and a water contact angle measurement. The Contact angle measurement shows that the TA modified membrane exhibits superhydrophilicity and underwater oleophobicity. Results from FTIR and XPS indicate that the carboxylic groups were formed on the surface of the TA modified membrane due to the oxidation of quinone by NaIO4, which is the key to superhydrophilicity of the TA modified membrane surface. In addition, the modified membrane was tested for oil-in-water emulsion separation. A high TOC rejection of 99% was achieved for different kinds of surfactant-stabilized oil-in-water emulsions as well as the surfactant-free oil/water mixture. The modified membrane not only showed a good water flux and oil/water separation performance but also exhibited excellent recyclability and chemical stability. Also, the developed method is versatile and can be applied to the different types of substrate material. This robust, simple, and green approach gives great potential to fabricate large-scale material surfaces for the industrial oily wastewater treatment.
    • Isobaric Combustion: A Potential Path to High Efficiency, in Combination with the Double Compression Expansion Engine (DCEE) Concept

      Babayev, Rafig (2018-11)
      The efficiency of an internal combustion engine is highly dependent on the peak pressure at which the engine operates. A new compound engine concept, the double compression expansion engine (DCEE), utilizes a two-stage compression and expansion cycle to reach ultrahigh efficiencies. This engine takes advantage of its high-integrity structure, which is adapted to high pressures, and the peak motored pressure reaches up to 300 bar. However, this makes the use of conventional combustion cycles, such as the Seiliger–Sabathe (mixed) or Otto (isochoric) cycles, not feasible as they involve a further pressure rise due to combustion. This study investigates the concept of isobaric combustion at relatively high peak pressures and compares this concept with traditional diesel combustion cycles in terms of efficiency and emissions. Multiple consecutive injections through a single injector are used for controlling the heat release rate profile to achieve isobaric heat addition. In this study, the intake pressure is varied to enable a comparison between the isobaric cases with different peak pressures, up to 150 bar, and the mixed cycle cases. Tests are performed at several different levels of EGR. The experiments are performed on a 12.8 L displacement 6-cylinder Volvo D13C500 engine utilizing a single cylinder with a standard 17-compression-ratio piston. In this study, the cylinder represents the high-pressure unit of the DCEE. The fuel used in all the experiments is a standard EU diesel. In each target condition, the different injection strategies are compared with the total amount of fuel kept relatively constant. The results prove that the isobaric combustion concept is feasible with a traditional injection system and can achieve gross indicated efficiencies close to or higher than those of a conventional diesel combustion cycle. Moreover, the results show that with an isobaric cycle, heat transfer losses can be reduced by over 20%. However, the exhaust energy is higher, which can eventually be recovered in the second stage of expansion. Thus, this cycle could be suitable for the DCEE concept. The CO, UHC and soot emission levels are proven to be fairly similar to those of the conventional diesel combustion. However, the NOx emissions are significantly lower for the isobaric combustion.
    • First assessment of viral diversity across corals from the central Red Sea suggests abundant association with Baculoviridae

      Ye, Jin (2018-11)
      Coral reefs are among the most diverse marine ecosystems, but they are threatened by climate change. The foundation of reef ecosystems is the coral holobiont or metaorganism that consists of the coral animal host, photosynthetic microalgae, bacteria, and viruses (among other organisms). While microalgae provide the energy for corals to build the massive three-dimensional skeletons, bacteria support functions related to metabolism, immunity, and environmental adaptation. Conversely, the function of viruses is less well understood. Although viruses were previously associated with coral disease and bleaching, we are missing an overall understanding of the diversity and identity of viruses associated with corals, in particular for understudied areas such as the Red Sea. Here we characterized coral-associated viral community composition using a large metagenomic and metatransciptomic dataset covering > 1 billion sequences across > 100 coral samples collected from 14 different coral species in the central Red Sea. The viral sequence portion shows that coral species significantly differ from each other, but the most abundant viral families were consistently present. Notably, we found a pervasive abundance of Baculoviridae in metagenomes. In contrast, Polydnaviridae were the most abundant viruses in metatranscriptomes, highlighting that the combined approach of metagenomics and metatranscriptomics is informative with regard to deciphering viral diversity and activity. Our study provides a first comprehensive description of viruses associated with Red Sea corals. In line with previous studies, we confirm the presence of Baculoviridae, Polydnaviridae, Phycodnaviridae, Mimiviridae, and Herpesviridae, which may be considered viral families that are globally and commonly associated with corals. The reason for the pervasive abundance of Baculoviridae in Red Sea corals at present remains unknown, but it is tempting to speculate that the association is related to the uniquely warm and salty environment of the Red Sea.
    • DNA Methylation in the Demosponge Amphimedon queenslandica is Involved in Genome Evolution and Transcription

      Ruiz Santiesteban, Juan Antonio (2018-11)
      DNA methylation is an epigenetic mechanism with roles that range from the fine tuning of transcription to genome wide dynamic acclimation to changing environments and regulation of developmental processes. While recent work has confirmed the presence and regulatory functions of DNA methylation in non-bilaterians, its role and distribution in Porifera has never been addressed. In this study, we performed whole genome bisulfite sequencing of the demosponge Amphimedon queenslandica and show that DNA methylation occurs mostly in CpG dinucleotides of coding regions. While high levels of gene-body methylation correlate positively with high expression and co-occur with the histone modification H3K36me3, they are not associated with amelioration of spurious transcription as found in other metazoans; nonetheless, per-exon methylation levels are predictive for exon retention suggesting a role in mRNA splicing. Additionally, analyses of Amphimedon and other sponges genomic data consistently revealed biased dinucleotide frequencies that suggest a long history of methylation-driven CpG conversion. Despite a genome wide loss of CpG dinucleotides, these are positively selected in exons and in methylated genes. These results indicate DNA methylation as a component of early metazoans regulome and challenge hypothesis on CpG methylation acting as a means for codon usage optimization.
    • Atmospheric Water Harvesting by an Anhydrate Salt and Its Release by a Photothermal Process Towards Sustainable Potable Water Production in Arid Regions

      Alsaedi, Mossab K. (2018-11)
      Only 2.5% of the water on Earth is fresh water and only less than 1% is accessible to human consumption. Landlocked and desert communities and communities that are not wealthy enough to provide clean drinking water via conventional water treatment technologies are facing severe water shortages and tend to rely on long distance transportation to supply fresh water for their daily use. As a lot of the water-scarce countries have abundant annual solar irradiation and relatively high humidity, this project proposes a technology that harvests water from ambient air using an anhydrate salt and releases it for collection using sunlight. This technology is designed to be potentially deployed in night-day cycles, as the humidity at night is at its peak, and solar irradiation during the day is also at its peak. In this work, a mesoporous silica powder filled with CuCl2 and coated with carbon nanotubes is used. The water capture performance of this material was investigated with different relative humidity environments. Furthermore, the powder agglomeration sizes of this material were also investigated for each relative humidity environment. Water release was investigated under 1 kW/m2 simulated solar light in an in-lab ~60% relative humidity environment. The results show that this mesoporous material was able to capture water at 12% relative humidity conditions, low enough to capture water from the air in the Sahara Desert. At relative humidity of 15% and 35%, the material was able to absorb 0.12 and 0.25 kg/kg of water, respectively, within 100 minutes, which indicates its fast water harvesting kinetics. A fully hydrated sample released 0.26 kg/kg of water in almost half an hour under 1 kW/m2 simulated sunlight. This project sheds more light on utilizing the atmosphere as an alternative water source.
    • Prediction of Active and Inactive Chemical Compounds from High-Throughput Assays

      Islam, Elaf J. (2018-11-28)
      This study considers chemical compounds that can exert their activity by interacting with a target protein or other molecular receptors. Our aim is to develop machine learning models that can predict if a chemical compound will be active in a particular test/assay. We will use data from assays that are present in the PubChem knowledgebase, specifically in its segment called BioAssays which reports the results of many high-throughput screening experiments. PubChem BioAssays is a valuable resource that contains information from a large number of experiments. In one assay, sometimes many hundreds or even many thousands of chemicals are tested. Data from these experimental assays contain information about chemicals that are active as well as chemicals that are not active in the assay. These represent an interesting resource of experimental data that are well suited for classification purposes. We will approach the problem by evaluating different ways that chemical compounds can be numerically described by means of so-called fingerprints, and then apply different machine learning (ML) and deep learning (DL) models to classify active and inactive chemicals for a number of assays. In this study, we will make comprehensive comparisons of the types of ML/DL models and types of fingerprint features that describe chemicals, and evaluate combinations of models and fingerprints that work best for the problem in question. Our focus is on finding those combinations which are useful for distinguishing active from inactive compounds in single PubChem assays. We will evaluate the methods across 10 assays and will examine the effects of 11 types of fingerprints. For example, PubChem fingerprints and MACCS keys fingerprints. For the evaluation, up to now we performed 88 experiments for each dataset and 968 in total for all 10 PubChem assays. These experiments involved approximately 6,000 interactions between chemicals and their targets. The implementation of this project has been done using MATLAB. Based on these and additional experiments, we will be in a position to propose which combination of fingerprints and ML/DL models works best in the above mentioned task. Such modeling will be useful to predict activity for chemicals that are not yet tested.
    • Multiple stressor interaction of nutrient enrichment and crude oil pollution on benthic recruitment on a Red Sea coral reef

      Hulver, Ann (2018-11)
      The Red Sea is one of the warmest, saltiest, and most oligotrophic seas in the world that supports a healthy and extremely diverse coral reef ecosystem. Increasing development along the Saudi Arabian coast may increase eutrophication due to impacts of human population and also oil pollution from increased shipping traffic and refinery activity. The risk of oil pollution combined with increased eutrophication due to coastal development provides a clear stressor interaction which is vastly understudied. Individually, these stressors are known to negatively impact coral reproduction, recruitment, and growth. This study focuses on reef settlement and recovery following experimentally-simulated disturbance scenarios. Carbonate recruitment tiles were placed on the reef and exposed to four treatments: control, nutrient enrichment with slow-release fertilizer, tiles soaked in crude oil, and a combination treatment of nutrient enrichment and oil-coated tiles. At periods of 3, 6, 9, 14, and 17 weeks, tiles were collected to classify the settled community and measure oxygen production. Oil, nitrate, and phosphate were the biggest determining factors predicting settlement and oxygen production of the different treatments. The oil treatment had the least overall settlement and oxygen production, whereas the nutrient treatment had the most turf algal recruitment and oxygen production. The combination treatment had an antagonistic effect on algal growth: the nutrients facilitated growth on the otherwise toxic oiled tiles.
    • Visualization and Simulation of Variants in Personal Genomes With an Application to Premarital Testing (VSIM)

      Althagafi, Azza Th. (2018-11-28)
      Interpretation and simulation of the large-scale genomics data are very challenging, and currently, many web tools have been developed to analyze genomic variation which supports automated visualization of a variety of high throughput genomics data. We have developed VSIM an automated and easy to use web application for interpretation and visualization of a variety of genomics data, it identifies the candidate diseases variants by referencing to four databases Clinvar, GWAS, DIDA, and PharmGKB, and predicted the pathogenic variants. Moreover, it investigates the attitude towards premarital genetic screening by simulating a population of children and analyze the diseases they might be carrying, based on the genetic factors of their parents taking into consideration the recombination hotspots. VSIM supports output formats based on Ideograms that are easy to interpret and understand, which makes it a biologist-friendly powerful tool for data visualization, and interpretation of personal genomic data. Our results show that VSIM can efficiently identify the causative variants by referencing well-known databases for variants in whole genomes associated with different kind of diseases. Moreover, it can be used for premarital genetic screening by simulating a population of offspring and analyze the disorders they might be carrying. The output format provides a better understanding of such large genomics data. VSIM thus helps biologists and marriage counsellor to visualize a variety of genomic variants associated with diseases seamlessly.
    • Catalytically Generating and Utilizing Hydrogen to Reduce NOx Emissions in Automobile Applications

      Alghamdi, Nawaf (2018-11)
      Heterogeneous catalysis is a powerful chemical technology because it can enhance the conversion of reactants, promote selectivity to a desired product, and lower the reaction temperature requirements. The breaking and forming of chemical bonds in heterogeneous catalysis is facilitated on a solid surface where adsorbed gas-phase species react and form products. This study is concerned with utilizing heterogeneous catalysis in the automobile industry via the generation and utilization of hydrogen to reduce NOx emissions. In spark ignition engines, the three-way-catalyst technology is ineffective at the more efficient, lean-burn conditions. In compression-ignition engines, an ammonia-based technology is implemented but has associated high cost and ammonia slip challenges. This motivates providing an alternative technology, such as hydrogen selective catalytic reduction (H2-SCR). In this study, four catalysts were investigated for the lean-burn selective catalytic reduction of NO using hydrogen. The catalysts were platinum (Pt) and palladium (Pd) noble metals supported on cerium oxide (CeO2) and magnesium oxide (MgO). Additionally, finding a source of hydrogen for H2-SCR on board a vehicle is a challenge due to the issues associated with hydrogen storage. A numerical study was performed to investigate the utilization of the partial oxidation of natural gas on a rhodium surface to synthesis gas, CO and H2. A kinetic understanding of natural gas demands an understanding of its components. While methane and ethane have been extensively studied, propane partial oxidation on rhodium has only been kinetically examined at low temperatures. The aim of the numerical study was to obtain an improved understanding of propane partial oxidation kinetics by extending the surface reactions mechanism to high temperatures and developing a gas phase mechanism to capture the effects of gas-phase reactions. Moreover, the optimal temperature and pressure for H2 generation were determined, and the kinetic simulation results were analyzed by temperature sensitivity, chemical path flux and hydrogen production sensitivity analyses.