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Novel metal–organic framework biosensing platform for detection of COVID-19 RNA
No full textThe latest pandemic resulting from the novel SARS-CoV-2 coronavirus has significantly affected public health, the worldwide economy, and social life. Metal organic frameworks (MOFs) are currently being implemented in biosensors for rapid and accurate detection of viruses thanks to their exceptional properties. This research aims to develop a Zeolitic Imidazolate Framework-8 (ZIF-8) based fluorescent biosensor for facile and rapid COVID-19 RNA sequence detection. ZIF-8 was characterized using several tests, such as FT-IR, TGA, and PXRD, to examine the MOF’s crystalline structure and thermal stability. The results demonstrated high crystallinity and thermal stability up to a temperature of 550 °C. The experimental study showed that ZIF-8 is an excellent fluorescence quencher, with 78.39% quenching efficiency. Analyzing the adsorption mechanism of probe DNA into ZIF-8 revealed that they can form electrostatic and π–π stacking interactions, forming a P-DNA@ZIF-8 complex and that PET is more dominant than FRET in the quenching mechanism. This ZIF-8 biosensing platform showed high sensitivity towards COVID-19 RNA with an ultra-low limit of detection of 6.24 pM, a rapid detection time of 8 min, and high selectivity to COVID-19 RNA. Indeed, ZIF-8 experienced much lower fluorescence recovery when tested on two mismatched RNAs. The experimental results show the potential use of ZIF-8 as a novel biosensor for a rapid and sensitive COVID-19 diagnosis.American University of SharjahDana Gas Endowed Research Chair fund.College of EngineeringCollege of Arts and SciencesDepartment of Chemical and Biological EngineeringDepartment of Mechanical EngineeringDepartment of Biology, Chemistry and Environmental Science
Experimental Investigation on the Effectiveness of EB-CFRP Confinement of Elliptical Concrete Columns
No full textThis paper presents the results of an experimental study involving 20 tests performed on elliptical concrete columns confined with externally bonded carbon fiber-reinforced polymer (EB-CFRP) laminates. The study aimed to evaluate the effects of elliptical aspect ratio (A/B) as well as confinement rigidity (number of EB-FRP layers) on confinement effectiveness. The experimental program consisted of one series of control concrete columns (unstrengthened) and three additional series, each one strengthened with one, two and three layers of EB-CFRP sheets, respectively. Furthermore, each series considered five elliptical aspect ratios (A/B) ranging from 1.0 to 1.6. Following compressive concentric tests until failure, the results were analyzed to characterize the confinement level with an increasing number of EB-CFRP layers as a function of the elliptical aspect ratio. The results show considerable enhancements in compressive strength and in the ductility of the confined columns. Furthermore, this improvement is amplified as the number of EB-CFRP layers increases, indicating a proportional relationship between the compressive strength and the number of CFRP layers. It is found that the ultimate strength of EB-CFRP-confined columns with three layers reached up to 130% compared to the control specimens. However, increasing the elliptical aspect ratio reduced the compressive strength and ductility of confined columns. This study investigated the relation between the CFRP hoop and axial strains and the elliptical aspect ratios. Moreover, through comparison, the results reveal that the prediction models proposed by the Canadian standards S806-12 and S6-19 do not capture the negative effect of the elliptical aspect ratio in confined concrete columns.Natural Sciences and Engineering Research Council of Canada (NSERC)Fonds de recherche du Québec—Nature et technologie (FRQNT)Deanship of Research and Graduate Studies (DRG) at Ajman Universit
Compressibility effects in microchannel flows between two-parallel plates at low reynolds and mach numbers: Numerical analysis
No full textUnder certain circumstances, flow in microchannels can exhibit compressibility effects even at Reynolds numbers (Re) around (below 2,300) and low Mach numbers (below 0.3). This is particularly true for gases, especially when the flow undergoes significant pressure changes or acceleration within the microchannel. This study investigates the compressibility effects encountered in two-parallel plates microchannels at these low Reynolds and Mach numbers, due to the high-pressure drop associated with the small scale of the microchannels. This uncommon flow is characterized by an exceptionally small channel diameter-to-length aspect ratio (∼10–3), resulting in a friction coefficient that deviates from the typical value for laminar flow between parallel plates (f = 96/Re). Both steady and transient effects on the flow field are examined under low Re subsonic flow, assuming continuum behavior. The ideal gas equation is used to model gas density, while the isothermal Tait-Murnaghan equation models liquid density. For gases, compressibility effects are observed primarily when the inlet pressure ratio exceeds 0.1. The results show that these effects are less pronounced for liquids, even at elevated inlet pressure ratios. Additionally, a flow delay across the channel exhibits a first-order transient response. For liquid flow, this effect depends on the channel resistance, the total fluid volume within the channel, and the liquid's bulk properties, rather than the inlet pressure ratio
Effect of Blended Lightweight and Normal Weight Aggregates on The Shear Capacity of Concrete Beams
No full textA Master of Science thesis in Civil Engineering by Khalid Hesham Khalil entitled, “Effect of Blended Lightweight and Normal Weight Aggregates on The Shear Capacity of Concrete Beams”, submitted in November 2024. Thesis advisor is Dr. Farid Abed and thesis co-advisor is Dr. Sherif Yehia. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This thesis investigates the influence of internal curing using lightweight aggregate (LWA) on the shear capacity, shrinkage, and cracking resistance of concrete beams compared to conventionally cured mixes. Internal curing, achieved by incorporating pre-saturated LWA, provides an internal moisture reservoir that enhances hydration, particularly in low-water mixes, mitigating shrinkage and improving structural performance. The concrete mix included Portland cement (SG 3.15), Pumice 4-8mm as LWA from Turkey (SG 1.45), dune sand (SG 2.61), crushed sand (SG 2.61), normal-weight aggregates of 10mm and 20mm (SG 2.7), GGBS (SG 2.9), and silica fume (SG 2.2). The experimental program evaluated mechanical properties such as modulus of rupture, tensile strength, and compressive strength. Six reinforced concrete beams were tested under four-point loading without shear reinforcement. The three concrete mixes were: (1) "CC," cured conventionally, (2) "ICC," combining internal and conventional curing, and (3) "IC," using LWA solely for internal curing. Beams were subjected to increasing loads to observe cracking and shear capacity, while shrinkage and creep tests evaluated long-term stability. Results showed internal curing significantly improved structural performance. The ICC mix exhibited a 43.45% increase in shear capacity over CC, while IC showed an 11.52% increase. Shrinkage tests showed reduced microstrain in internally cured samples, confirming better volumetric stability. Creep tests revealed reduced long-term deformation, enhancing durability. This study highlights internal curing with LWA as an effective method to improve concrete performance, particularly in thick or sealed sections where external curing is less effective. However, proper LWA preparation is crucial to ensure sufficient moisture without compromising workability. These findings establish internal curing as a viable approach to enhancing shear capacity, reducing shrinkage, and improving durability for demanding structural applications.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Development of High-Strength Conductive Concrete Mix Using Locally Available Materials
No full textA Master of Science thesis in Civil Engineering by Obida Othman entitled, “Development of High-Strength Conductive Concrete Mix Using Locally Available Materials”, submitted in January 2024. Thesis advisor is Dr. Sherif Yehia and thesis co-advisors are Dr. Nasser Qaddoumi and Dr. Mohamed Elchalakani. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Civil EngineeringMultidisciplinary ProgramsMaster of Science in Civil Engineering (MSCE
Navigating Anti Money Laundering Complexities: Evidence from the UAE
No full textA Master of Business Administration (MBA) thesis by Abdulla Obaid Almheiri entitled, “Navigating Anti Money Laundering Complexities: Evidence from the UAE”, submitted in December 2024. Thesis advisor is Dr. Kimberly C. Gleason and thesis co-advisor is Dr. Zaher Zantout. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).The ever-changing global financial system poses complex problems in the fields of Anti-Money Laundering and Countering the Financing of Terrorism. The critical geopolitical location of the United Arab Emirates and it being one of the largest global financial centers make the country distinctive in its efforts to enhance its Anti Money Laundering frameworks to align with international and Financial Action Task Force regulations. The UAE's recent gray listing by the Financial Action Task Force on 4 March. 2022 compelled the country to make an urgent decision regarding stepping up its compliance efforts. This thesis will clarify the contributions of the United Arab Emirates concerning the Anti-Money Laundering and Combating Financing of Terrorism and highlight the country's regulatory, operational, and international cooperation. It assesses the country’s current frameworks in light of the Task Force Recommendations. The thesis considers the various strategic actions that the Country takes towards improving its Frameworks in terms of legislative reforms, institutional improvements, and more substantial international cooperation. While preparing this research, the country took significant steps to enhance the Anti money laundering landscape and fulfill the financial action task force recommendations, resulting in the Country being subsequently removed from the Grey List on 23 February 2024. The grounded theory methodology is used in this research through content analysis of regulatory documents and expert interviews designed to give an inclusive picture of the landscape in the United Arab Emirates. The findings of this thesis will be relevant for policymakers and financial institutions in the country if put into a dynamic framework, which should enable the decision-makers to improve the current practices in line with the dynamic standards of the financial action task force while not hindering the business environment. it will also aim to construct a detailed approach framework on what tools and policies will be implemented within the local financial sector to adhere to the guidelines and maintain the white-list status.School of Business AdministrationDepartment of Management, Strategy and EntrepreneurshipMaster of Business Administration (MBA
Soiling Detection on Solar Panels Using Artificial Intelligence
No full textA Master of Science thesis in Engineering Systems Management by Hussein Mohammad Ali Kaya entitled, “Soiling Detection on Solar Panels Using Artificial Intelligence”, submitted in December 2024. Thesis advisor is Dr. Zied Bahroun and thesis co-advisor is Dr. Noha Hussein. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The demand of energy has shown a significant increase worldwide over the past few years. Solar energy is one source that can be the solution of our future. One of the most significant issues that has a substantial impact on the solar panel is soiling. Soiling accumulation generates losses in energy efficiency and decreases the electricity output. Several research papers have worked on proposing systems to investigate this issue. However, there is a lack of analysis regarding the inspection tools that lead to selecting the optimal ones. In this research, a new system of inspection tools and a model is proposed to detect the soiling on solar panel. The objective of this study is to provide a low-cost system that integrates between low-cost inspection tools and an accurate model to assist in precise detection of soiling on solar panel. Different inspection tools were examined experimentally to assess their performance and ability to detect soiling. Two setups were conducted, a low-cost system setup and a high-cost system setup, Additionally, a machine learning was utilized to train different models, to come up with a model with high accuracy for processing the collected data to detect soiling. Finally, Multi-Attribute Utility Theory (MAUT) was applied to obtain the most feasible and optimal combination of tools for the proposed system. As a result, a configuration comprising a voltage sensor (0-25V), high-cost current sensor 30A, and low-cost dust sensor GP2Y1010AU0F, was selected using MAUT and trained using machine learning. The Gaussian process regression model demonstrated high accuracy value for the proposed system, achieving an R-squared value of 99% and an RMSE value of 0.0022784.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM
Piezoelectric Energy Harvesting for Leadless Pacemakers: The Investigation of Patients' ECGs
No full textThis paper investigates the performance of a novel heart piezoelectric energy harvester. Heart-simulating experiments were based on the electrocardiogram (ECG) signals from different patients. The shape of the ECG signal as the heart motion simulation was investigated for the energy harvester performance. Amplitude-normalized ECG signals of five patients were used as input for a vibration shaker while the electrical performance was recorded. The output results, voltage, the number of energy pulses generated, and the width of the generated energy pulses were calculated. Results showed that this novel energy harvester developed 11.40 ± 0.85 V voltage, 26.4 pulses of energy in each heartbeat, and an average pulse width of 0.11 ±0.03 ms. The results showed that the output performance of different patients is still influential. The study contributes to broadly testing piezoelectric energy harvesters for leadless pacemakers
Deep Learning for the Accurate Prediction of Triggered Drug Delivery
No full textThe need to mitigate the adverse effects of chemotherapy has driven the exploration of innovative drug delivery approaches. One emerging trend in cancer treatment is the utilization of Drug Delivery Systems (DDSs), facilitated by nanotechnology. Nanoparticles, ranging from 1 nm to 1000 nm, act as carriers for chemotherapeutic agents, enabling precise drug delivery. The triggered release of these agents is vital for advancing this novel drug delivery system. Our research investigated this multifaceted delivery capability using liposomes and metal organic frameworks as nanocarriers and utilizing all three targeting techniques: passive, active, and triggered. Liposomes are modified using targeting ligands to render them more targeted toward certain cancers. Moieties are conjugated to the surfaces of these nanocarriers to allow for their binding to receptors overexpressed on cancer cells, thus increasing the accumulation of the agent at the tumor site. A novel class of nanocarriers, namely metal organic frameworks, has emerged, showing promise in cancer treatment. Triggering techniques (both intrinsic and extrinsic) can be used to release therapeutic agents from nanoparticles, thus enhancing the efficacy of drug delivery. In this study, we develop a predictive model combining experimental measurements with deep learning techniques. The model accurately predicts drug release from liposomes and MOFs under various conditions, including low- and high-frequency ultrasound (extrinsic triggering), microwave exposure (extrinsic triggering), ultraviolet light exposure (extrinsic triggering), and different pH levels (intrinsic triggering). The deep learning-based predictions significantly outperform linear predictions, proving the utility of advanced computational methods in drug delivery. Our findings demonstrate the potential of these nanocarriers and highlight the efficacy of deep learning models in predicting drug release behavior, paving the way for enhanced cancer treatment strategies.American University of SharjahAl-Jalila FoundationAl Qasimi FoundationPatient’s Friends Committee-SharjahBiosciences and Bioengineering Research InstituteGulf Cooperation Council (GCC) Co-Fund ProgramTakamul ProgramTechnology Innovation Pioneer (TIP) Healthcare AwardsSheikh Hamdan Awards for Medical SciencesFriends of Cancer Patients (FoCP)Dana Gas Endowed Chair for Chemical Engineerin
Zeolitic Imidazolate Framework-Based Biosensing Platform for Detection of Covid-19 RNA
No full textA Master of Science thesis in Chemical Engineering by Aya Tarek Elgazar entitled, “Zeolitic Imidazolate Framework-Based Biosensing Platform for Detection of Covid-19 RNA”, submitted in May 2024. Thesis advisors are Dr. Rana Sabouni and Dr. Mehdi Ghommem. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The recent outbreak caused by the novel coronavirus SARS-CoV-2 has led to a global pandemic with significant effects on public health, the global economy, and social life. Rapid and accurate diagnosis methods are important in reducing the spread of viruses and preventing future outbreaks. Recently, Metal Organic Frameworks (MOFs) have gained great interest as biosensors for virus detection. This thesis aims to develop a Zeolitic imidazolate framework-8 (ZIF-8) based fluorescent biosensor for detecting the COVID-19 RNA sequence. Commercial and microwave-synthesized ZIF-8s were tested as potential detector materials. Commercial and MW ZIF-8s were characterized using several tests such as TGA, XRD, FT-IR, and N2 adsorption/desorption isotherms to examine the MOF’s crystalline structure and thermal stability. The results illustrated that commercial ZIF-8 and MW ZIF-8 had high crystallinity and thermal stability up to a temperature of 550 oC and 400 oC, respectively. The experimental study showed that both ZIF-8s exhibited excellent quenching properties, with quenching efficiencies of 78.39% and 72.14% for commercial ZIF-8 and microwave-synthesized ZIF-8, respectively. Further analysis of the adsorption mechanism of P-DNA into the MOFs, revealed that they can form electrostatic and π- π stacking interactions, forming a P-DNA@ZIF-8 complex. The biosensing platform of ZIF-8 showed high sensitivity towards COVID-19 RNA with a very low limit of detection of 6 pM and 12 pM for commercial and MW ZIF-8, respectively. The results suggest that this ZIF-8-based biosensor has the potential for a rapid and sensitive COVID-19 diagnosis.College of EngineeringDepartment of Chemical and Biological EngineeringMaster of Science in Chemical Engineering (MSChE