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Development of Liposome-Based Immunoassay for the Detection of Cardiac Troponin I
No full textCardiovascular diseases (CVDs) are one of the foremost causes of mortality in intensive care units worldwide. The development of a rapid method to quantify cardiac troponin I (cTnI)—the goldstandard biomarker of myocardial infarction (MI) (or “heart attack”)—becomes crucial in the early diagnosis and treatment of myocardial infarction (MI). This study investigates the development of an efficient fluorescent “sandwich” immunoassay using liposome-based fluorescent signal amplification and thereby enables the sensing and quantification of serum-cTnI at a concentration relevant to clinical settings. The calcein-loaded liposomes were utilized as fluorescent nano vehicles, and these have exhibited appropriate stability and efficient fluorescent properties. The standardized assay was sensitive and selective towards cTnI in both physiological buffer solutions and spiked human serum samples. The novel assay presented noble analytical results with sound dynamic linearity over a wide concentration range of 0 to 320 ng/mL and a detection limit of 6.5 ng/mL for cTnI in the spiked human serum.American University of Sharja
Detection of Double and Triple Compression in Videos for Digital Forensics Using Machine Learning
No full textA Master of Science thesis in Computer Engineering by Seba Youssef entitled, “Detection of Double and Triple Compression in Videos for Digital Forensics Using Machine Learning”, submitted in December 2020. Thesis advisor is Dr. Tamer Shanableh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Digital video forensics is the process of analysing, examining and comparing a video for use in legal matters and court cases. In digital video forensics, the main aim is to detect and identify video forgery and manipulation to ensure a video’s authenticity and reliability for use in court. This work focuses on passive forensics techniques, namely compression-based digital video forensics. When a video is edited by methods such as frame deletion, cropping, or duplication, the original encoded bitstream is first decoded, editing is applied and then the video is re-compressed before saving it. This means that by detecting re-compression in videos, we can interpret that the video has undergone some form of manipulation. The least number of recompressions a video can have is double compression, the first results from the device initially capturing the video which compresses it to store it in a suitable format and the second comes from the editing software or tool that re-compresses the video after it has been edited. Such editing can also be done multiple times leading to multiple compressions. Thus, finding out the compression history of a video becomes a very important mean for detecting any manipulation. Several techniques have been studied and investigated for the accurate classification of double and triple compression in videos based on machine learning and deep learning models with promising results being obtained. In this work, a number of experiments are conducted by using K-Nearest Neighbours (KNN), Random Forest (RF) or bi-directional Long Short-Term Memory (bi-LSTM) classifiers on a dataset of forged and unforged video sequences. In each of the experiments, performance is evaluated based on the classification accuracy and confusion matrix. Experiments are conducted on MPEG2 and HEVC coded videos using the same re-compression quantization parameter and the results of recompression detection are compared. Experiments are also conducted on HEVC coded videos with the same recompression bitrate and the results obtained are compared to existing solutions in literature. The experimental results revealed that both double compression and triple compression can be accurately detected using the proposed machine learning and deep learning solutions.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Development and Testing of a Novel MOF-based Composite for MEMS Sensing Applications
No full textA Master of Science thesis in Biomedical Engineering by Bassam Jihad El Taher entitled, “Development and Testing of a Novel MOF-based Composite for MEMS Sensing Applications”, submitted in November 2020. Thesis advisor is Dr. Mehdi Ghommem and thesis co-advisor is Dr. Rana Sabouni. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Mercury is one of the most hazardous environmental pollutants due to its immediate health implications on humans. With the potential of pollution of water due to industrial activities, a need for assessment of mercury levels in waters is needed. Metal organic frameworks (MOFs) have emerged as a new class of crystalline porous materials with potential deployment for chemical detection thanks to their outstanding features. This thesis presents the synthesis of a novel MOF namely NH2-Cd-BDC that was successfully developed and investigated toward mercury detection in a competitive aqueous medium in presence of other metal ions. NH2-Cd-BDC is composed of Cadmium ions (Cd²⁺) as the metal cluster and 2-aminoterephthalic acid (NH2-H2BDC) as the organic linker. The luminescent property of the MOF provides a cost-effective and nondestructive method for testing the detection ability of the MOF using fluoro-spectroscopy. The experiments showed that the developed MOF has a limit of detection (LOD) of 0.58 μM and demonstrated the superiority of mercury detection in comparison to other metal ions including Na⁺, K⁺, Ca²⁺, Crᵌ⁺, Cd²⁺, Cu²⁺, Pbᵌ⁺ and Feᵌ⁺. Several characterization tests of the novel developed MOF were executed including XRD, FTIR, TGA, FE-SEM and SEM to inspect its crystalline structure and thermal stability. The experimental study revealed that the MOF has a crystalline sea-shell shape, providing a large pore size for the mercury to be trapped in. To investigate how the NH2-Cd-BDC synthesized stands against other reported MOFs in the literature, three other MOFs, namely NH2-MIL53(Al), NH2-MIL88(Fe) and NH2-UiO-66(Zr), were prepared using microwave-assisted synthesis procedure and their capability to absorb mercury was investigated. All three MOFs comprise the same organic linker (NH2-H2BDC) but different metal clusters, Alᵌ⁺, Zr²⁺+ and Feᵌ⁺. All the three MOFs are characterized using XRD, FTIR, FE-SEM and TGA. Similar to the novel MOF, the performance of the other three MOFs was assessed by experimenting their capability to detect mercury in presence of aforementioned metals ions. The LOD values were found equal to 0.51 μM, 1.03 μM and 1.94 μM for NH2-MIL53(Al), NH2-MIL88(Fe) and NH2-UiO-66(Zr), respectively. This indicates the suitability of the NH2-Cd-BDC MOF for mercury sensing applications.College of EngineeringMultidisciplinary ProgramsMaster of Science in Biomedical Engineering (MSBME
Development and Characterization of Novel Composite and Flexible Electrode Based on Titanium Dioxide
No full textFlexible implantable bioelectrodes have the potential to advance neural sensing and muscle stimulation, especially in peripheral nerve injuries. In such cases, the application of electrical stimulation to muscles prevents muscular atrophy and helps to bridge the gap between the injured nerve and the corresponding muscle. This work investigates the fabrication and characterization of a novel, cost effective, flexible bioelectrodes, based on silicone polymer (polysiloxane) and titanium (IV) dioxide. Samples were synthesized and evaluated for their electrochemical and mechanical properties. The bioelectrodes fabricated in this work exhibited promising electrical and mechanical characteristics. The ductile properties for the samples showed an elongation of 293% ± 27.1% before breaking and an elastic modulus of 32.9 ± 5.01 kPa. The impedance at 1 kHz (a standard frequency value to measure the neural activity) was equal to 198 kΩ. The lowest electrode impedance found at 7 MHz was 0.35 kΩ. Thus, supporting its' potential to be employed in implantable electrode applications
Investigations of the Co-Pt alloy phase diagram with neutron diffuse scattering, inverse cluster variation method, and Monte Carlo simulations
No full textThe short-range order in a CoPt alloy was determined at 1203 and 1423 K using neutron diffuse scattering measurements. The effective pair interactions provided by data analysis reproduce well the experimental order-disorder transition temperature in Monte Carlo simulations. They complete previous results reported for the Co-Pt system and are compared to those obtained within tight-binding and ab initio formalisms. Our results show that the important dependence of the nearest-neighbor pair interactions with composition is not related to the sample magnetic state at the measured temperatures. Interactions measured in the paramagnetic domain for the CoPt alloy behave like those in the ferromagnetic domain for the Co₃Pt and Co₀․₆₅Pt₀․₃₅ alloys. The effective pair interactions related to the tight-binding Ising model provide a relatively good description of the CoPt alloy thermodynamics close to the ordering temperature (short-range order and temperature of phase transformation), even if they strongly differ from those measured in this study. The average magnetic moment of Co atoms at high temperatures was determined from the analysis of the intensity contribution that is not dependent on the scattering vector. The obtained value is very close to the moment measured at room temperature or determined from ab initio calculations. This confirms the Curie-Weiss behavior of the CoPt alloy. Finally, transmission electron microscope observations carried out on samples annealed for about 30 days confirmed that the order-disorder transition takes place in the 830–843 K temperature interval at the Co₃Pt composition
Skills and Competencies for Effective Academic Advising and Personal Tutoring
No full textAdvising/personal tutoring has moved from the fringes of higher education to the center of student success initiatives. Advising professionals serve as faculty members, mentors, student advocates, and campus leaders. Drawing upon data from an empirical investigation regarding the professionalization of academic advising, we examine the critical aspects related to performing effective academic advising and personal tutoring. Using directed qualitative content analysis, data were examined for evidence of professional values, professional skills, professional behaviors, training, and continuing professional education and development. We consider the findings in comparison to NACADA’s Core Values, the John N. Gardner Institute for Excellence in Undergraduate Education in support of student success by promoting excellence in academic advising (EAA), NACADA’s Core Competencies of Academic Advising, Council for the Advancement of Standards in Higher Education (CAS) Standards, UKAT Professional Framework for Advising and Tutoring, and United Kingdom’s National Occupational Standards.NACADA: The Global Community of Academic Advisin
Theft Detection Unit For Photo-Votaic Generation in Smart Grid Networks
No full textA Master of Science thesis in Electrical Engineering by Nouf Ahmad Almadani entitled, “Theft Detection Unit for Photo-Voltaic Generation in Smart Grid Networks”, submitted in May 2020. Thesis advisors are Dr. Mostafa Shaaban and Dr. Usman Tariq. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).While the increased connectivity of the power grid has allowed for the automation of its functionality, it has also led to a heightened vulnerability to cyber threats, putting the whole power system security at risk of energy theft through the manipulation of data. In addition, the introduction of the smart grid allows customers to have their own power-generating units, which are usually photovoltaic (PV) panels. With two-way communication under the smart grid paradigm, customers’ local generation can be measured by smart meters and reported to the utility, which in turn pays customers for their generated electricity. Manipulating smart meters to report false generated electricity is a growing concern that can jeopardize a utility’s revenues. Thus, the objective of this work is to design and build an intelligent theft detector unit for PV injection (TDUPV) that detects suspicious data flow from customers’ solar smart meters to the back-end system within the utility. This topic contributes to the theft detection research community as it considers the injection of PV panels, which had not been considered in any previous research work. The detector is based on a regression tree model that utilizes weather information and customers’ PV injections to predict the honesty of the injected power from customers’ PV panels reported by the solar smart meters, assuming a data flow manipulated by cyberattacks. The mechanism of detection is based on the probability density function (PDF) of the error between the actual and predicted values. The performance of the TDUPV was evaluated by testing several case studies under different theft scenarios and shows the effectiveness of the proposed unit.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Facile Ultrasound-Triggered Release of Calcein and Doxorubicin from Iron-Based Metal-Organic Frameworks
No full textMetal-organic frameworks (MOFs) are promising new nanocarriers with potential use in anticancer drug delivery. However, there is a scarcity of studies on the uptake and release of guest molecules associated with MOF nanovehicles, and their mechanism is poorly understood. In this work, newly developed iron-based MOFs, namely Fe-NDC nanorods, were investigated as potential nanocarriers for calcein (as a model drug/dye) and Doxorubicin (a chemotherapeutic drug (DOX)). Calcein was successfully loaded by equilibrating its solution with the MOFs nanoparticles under constant stirring. The calcein average encapsulation efficiency achieved was 43.13%, with a corresponding capacity of 17.74 wt.%. In-vitro calcein release was then carried out at 37 °C in phosphate buffer saline (PBS) using ultrasound (US) as an external trigger. MOFs released an average of 17.8% (without US), whereas they released up to 95.2% of their contents when 40-kHz US at ∼1 W/cm² was applied for 10 min. The cytostatic drug DOX was also encapsulated in Fe-NDC, and its In-vitro release profile was determined under the same conditions. DOX encapsulation efficiency and capacity were found to be 16.10% and 13.37 wt.%, respectively. In-vitro release experiments demonstrated significant release, reaching 80% in 245 minutes, under acoustic irradiation, compared to around 6% in the absence of US. Additionally, experimental results showed that Fe-NDC nanoparticles are biocompatible even at relatively high concentrations, with an MCF-7 IC₅₀ of 1022 μg/ml. Our work provides a promising platform for anticancer drug delivery by utilizing biocompatible Fe-NDC nanoparticles and US as an external trigger mechanism
Weighted multimodal family of distributions with sine and cosine weight functions
No full textIn this paper, the moment of various types of sine and cosine functions are derived for any random variable. For an arbitrary even probability density function, the sine and cosine moments are used to define new families of univariate multimodal probability density and their corresponding characteristic functions. For illustration, two weighted multimodal generalizations of the t distribution are investigated. Furthermore, a method of calculating some interesting improper integrals is also presented. Finally, an explicit expression of the probability density function of the sum of independent t-distributed random variables with odd degrees of freedom is derived.American University of Sharja
Modeling of fiber bridging in fluid flow for well stimulation applications
No full textAccurate acid placement constitutes a major concern in matrix stimulation because the acid tends to penetrate the zones of least resistance while leaving the low-permeability regions of the formation untreated. Degradable materials (fibers and solid particles) have recently shown a good capability as fluid diversion to overcome the issues related to matrix stimulation. Despite the success achieved in the recent acid stimulation jobs stemming from the use of some products that rely on fiber flocculation as the main diverting mechanism, it was observed that the volume of the base fluid and the loading of the particles are not optimized. The current industry lacks a scientific design guideline because the used methodology is based on experience or empirical studies in a particular area with a particular product. It is important then to understand the fundamentals of how acid diversion works in carbonates with different diverting mechanisms and diverters. Mathematical modeling and computer simulations are effective tools to develop this understanding and are efficiently applied to new product development, new applications of existing products or usage optimization. In this work, we develop a numerical model to study fiber dynamics in fluid flow. We employ a discrete element method in which the fibers are represented by multi-rigid-body systems of interconnected spheres. The discrete fiber model is coupled with a fluid flow solver to account for the inherent simultaneous interactions. The focus of the study is on the tendency for fibers to flocculate and bridge when interacting with suspending fluids and encountering restrictions that can be representative of fractures or wormholes in carbonates. The trends of the dynamic fiber behavior under various operating conditions including fiber loading, flow rate and fluid viscosity obtained from the numerical model show consistency with experimental observations. The present numerical investigation reveals that the bridging capability of the fiber–fluid system can be enhanced by increasing the fiber loading, selecting fibers with higher stiffness, reducing the injection flow rate, reducing the suspending fluid viscosity or increasing the attractive cohesive forces among fibers by using sticky fibers