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The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment
No full textPrecision medicine is emerging as an integral component in delivering care in the health system leading to better diagnosis and optimizing the treatment of patients. This growth is due to the new technologies in the data science field that have led to the ability to model complex diseases. Precision medicine is based on genomics and omics facilities that provide information about molecular proteins and biomarkers that could lead to discoveries for the treatment of patients suffering from various diseases. However, the main problems related to precision medicine are the ability to analyze, interpret, and integrate data. Hence, there is a lack of smooth transition from conventional to precision medicine. Therefore, this work reviews the limitations and discusses the benefits of overcoming them if big data tools are utilized and merged with precision medicine. The results from this review indicate that most of the literature focuses on the challenges rather than providing flexible solutions to adapt big data to precision medicine. As a result, this paper adds to the literature by proposing potential technical, educational, and infrastructural solutions in big data for a better transition to precision medicine
Why and when do family firms invest less in talent management? The suppressor effect of risk aversion
No full textThis article explores the complex relationship between family firms and talent management practices. We use an international sample of medium-sized manufacturing firms to show that the relationship between family-owned firms and investment in talent management practices is mediated by the firm's level of risk aversion, which is, in turn, moderated by industry competition. Risk-averse family-owned firms tend to invest less in talent management practices when industry competition is weak. In contrast, when competition increases, family-owned firms tend to invest in talent as much as non-family-owned firms do.Alma Mater Studiorum - Università di Bologn
Generative Deep Learning to Detect Cyberattacks for the IoT-23 Dataset
No full textThe rapid growth of Internet of Things (IoT) is expected to add billions of IoT devices connected to the Internet. These devices represent a vast attack surface for cyberattacks. For example, these IoT devices can be infected with botnets to enable Distributed Denial of Service (DDoS) attacks. Signature-based intrusion detection systems are traditional countermeasures for such attacks. However, these methods rely on human experts and are time-consuming in terms of updates and may not exhaust all attack types especially zero-day attacks. Deep learning has shown some promise in intrusion detection. This paper shows that it is possible to use generative deep learning methods like Adversarial Autoencoders (AAE) and Bidirectional Generative Adversarial Networks (BiGAN) to detect intruders based on an analysis of the network data. The recently posted full IoT-23 dataset based on Somfy door lock, Philips Hue and Amazon Echo devices was used to train generative deep learning models to detect a variety of attacks like DDoS, and various botnets like Mirai, Okiruk and Torii. Over 1.8 million network flows were used to train the various models. The resulting generative models outperform traditional machine learning techniques like Random Forests. Both AAE and BiGAN-based models were able to achieve an F1-Score of 0.99. A BiGAN to detect unknown attacks was also trained to detect novel zero-day attacks with an F1-Score from 0.85 to 1.American University of Sharja
A Simulation Study of the Role of Mechanical Stretch in Arrhythmogenesis during Cardiac Alternans
No full textThe deformation of the heart tissue due to the contraction can modulate the excitation, a phenomenon referred to as mechanoelectrical feedback (MEF), via stretch-activated channels. The effects of MEF on the electrophysiology at high pacing rates are shown to be proarrhythmic in general. However, more studies need to be done to elucidate the underlying mechanism. In this work, we investigate the effects of MEF on cardiac alternans, which is an alternation in the width of the action potential that typically occurs when the heart is paced at high rates, using a biophysically detailed electromechanical model of cardiac tissue. We observe that the transition from spatially concordant alternans to spatially discordant alternans, which is more arrhythmogenic than concordant alternans, may occur in the presence of MEF and when its strength is sufficiently large. We show that this transition is due to the increase of the dispersion of conduction velocity. In addition, our results also show that the MEF effects, depending on the stretch-activated channels’ conductances and reversal potentials, can result in blocking action potential propagation.Natural Sciences and Engineering Research Council of CanadaAmerican University of Sharja
Biomedical Applications of Metal−Organic Frameworks for Disease Diagnosis and Drug Delivery: A Review
No full textMetal−organic frameworks (MOFs) are a novel class of porous hybrid organic−inorganic materials that have attracted increasing attention over the past decade. MOFs can be used in chemical engineering, materials science, and chemistry applications. Recently, these structures have been thoroughly studied as promising platforms for biomedical applications. Due to their unique physical and chemical properties, they are regarded as promising candidates for disease diagnosis and drug delivery. Their well-defined structure, high porosity, tunable frameworks, wide range of pore shapes, ultrahigh surface area, relatively low toxicity, and easy chemical functionalization have made them the focus of extensive research. This review highlights the up-to-date progress of MOFs as potential platforms for disease diagnosis and drug delivery for a wide range of diseases such as cancer, diabetes, neurological disorders, and ocular diseases. A brief description of the synthesis methods of MOFs is first presented. Various examples of MOF-based sensors and DDSs are introduced for the different diseases. Finally, the challenges and perspectives are discussed to provide context for the future development of MOFs as efficient platforms for disease diagnosis and drug delivery systems.American University of SharjahPatient's Friends Committee-SharjahAlJalila FoundationAl Qasimi FoundationTechnology Innovation Pioneer-Healthcare ProgramTakamul ProgramHamdan Bin Rashid Al Maktoum Award for Medical SciencesDana Gas Endowed Chair for Chemical Engineerin
Nonlinear Bending and Snapthrough Response of Doubly Curved Laminated Shells
No full textA Master of Science thesis in Mechanical Engineering by Hooman Aminipour entitled, “Nonlinear Bending and Snapthrough Response of Doubly Curved Laminated Shells”, submitted in April 2021. Thesis advisor is Dr. Samir Emam. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Shell structures made up of conventional fiber reinforced composite (FRC) laminates find many applications in engineering fields. In contrary to plate structures, shells exhibit two stable equilibrium configurations. Due to excessive loading, shells may largely deform and hence snap from one equilibrium position to the other. Snapthrough or snapback motion involves large deflections and hence it is inherently a nonlinear phenomenon. In this thesis, the nonlinear static response of simply supported doubly curved FRC shells is explored according to the classical laminated theory (CLT) with von Karman geometric nonlinearity. Various types of composites are considered: unidirectional [0₄], symmetric [0,90]ₛ, unsymmetric [0,0,90,90] and antisymmetric [0,90,0,90] laminates. The equations of motion and the associated boundary conditions are derived using the Hamilton’s principle. The axial displacements are eliminated from equations of motion by utilizing the Airy stress function and the nonlinear compatibility equation. This reduces the governing equations to two: the compatibility equation and the equation of motion governing the transverse deformation. The Galerkin’s approach is used to obtain a reduced-order model (ROM). This discretization leads to a set of nonlinear coupled ordinary differential equations (ODEs). Three modes are retained in the discretization. By setting all time-dependent terms equal to zero, the system of ODEs reduces to a set of nonlinearly coupled algebraic equations which are solved by means of the Newton-Raphson method for the static equilibrium positions and the Jacobian method is used to assess their stability. The effect of the stacking sequence, radii of curvature, curvature ratio and the shell thickness on the nonlinear bending and snapthrough response are investigated.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Characterization of heavy vehicle headways in oversaturated interrupted conditions: Towards development of passenger car equivalency factors
No full textPassenger car equivalency (PCE) of heavy trucks is often studied using filed observation and microscopic simulation models, especially for signalized intersections. While the Highway Capacity Manual recommends a single value regardless of the percentage of those heavy vehicles, literatures have shown that this equivalency is affected by different factors, including the trucks percentage. This research aims to examine the PCE under different level of traffic and heavy trucks demands. First, field measurements were collected and used to examine the characteristics of heavy vehicle and passenger car headways in oversaturated interrupted flow conditions. Field observations were then used to calibrate a microscopic simulation model. The model was then used to evaluate impact on headways of different levels of congestion and heavy vehicle percentages. Field results show that truck headways are about 2.3 those of passenger cars. The results also show that trucks are 1.5 more likely to be first in a queue when compared to passenger cars and 1.7 times more likely to be in first four vehicles in a standing queue. Passenger cars immediately behind trucks had longer than average headway. The simulation results suggest that PCE increases nonlinearly with increase in congestion level and with percentage of trucks; PCE's increase becomes less marked once sever congestion (stop-and-go with increasing queue lengths) conditions set in
Influence of Foundation Rigidity on the Structural Response of Mat Foundation
No full textA mat is a type of shallow foundation that is appropriate for structures supported on soil having relatively low bearing capacity or excessive settlement. Structural analysis of a mat foundation can be accomplished by either assuming the mat to be perfectly rigid or by considering the soil-structure interaction. This study researches the relationship between the mat-soil rigidity and structural response in terms of the soil bearing pressure, bending moment, and shear within the mat. To accomplish the objective of the study, 70 different mats are analyzed using a linearly elastic finite element approach. The variables that are considered in the analysis are the number of bays in each direction, center-to-center column spacing, mat thickness, panel aspect ratio, column cross section dimensions, soil modulus of subgrade reaction, and modulus of elasticity of concrete. A dimensionless mat rigidity measure was developed that determines whether a given mat can be reasonably analyzed by assuming it to be infinitely rigid. The developed rigidity factor takes into consideration all parameters that significantly affect the mat structural response. Results of the analysis indicate that there is strong correlation between the developed rigidity factor and critical soil bearing pressure and maximum internal bending moment within the mat. No correlation was observed between the mat rigidity and critical shear force. Relationships between the rigidity factor and the critical soil bearing pressures and bending moments, relative to the response of the infinitely rigid mat, are proposed. A parametric study is included to demonstrate the impact of the variables that affect the rigidity index on the response of the mat.American University of Sharja
Use of Ionic Liquids for Produced Water Treatment
No full textA Master of Science thesis in Chemical Engineering by Shehzad Liaqat entitled, “Use of Ionic Liquids for Produced Water Treatment”, submitted in December 2021. Thesis advisor is Dr. Taleb Ibrahim. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Produced water (PW) has adverse effects on human health and aquatic life. Finding a viable method for the efficient extraction of oil from PW is a challenging task for environmental researchers. In this work, various ionic liquids (ILs) having bis(trifluoromethylsulfonyl)imide (NTf2) anion with different cations such as imidazolium, ammonium, phosphonium, and pyridinium were employed for the removal of oil from PW through liquid-liquid extraction (LLE). Clay-alginate beads loaded with ILs were also applied as adsorbents via the adsorption process. The effect of ILs structure on the removal efficiency of ILs was examined. The effects of several process parameters such as initial concentration of oil, contact time, pH, phase ratio, and temperature on the removal efficiency of ILs were analyzed and optimized. Different characterization such as Fourier transform infrared spectrophotometer (FTIR), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and thermal gravimetric analysis (TGA) were used to investigate the surface morphology, chemical bond structure and functional group, and thermal stability of the used materials, respectively. Results revealed that 1-decyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide [C10Mim][NTf2] is the best ionic liquid (IL) among the studied ILs at optimum conditions (500 ppm initial oil concentration, 4 min contact time, 8 pH, and at room temperature) with a removal efficiency of 92.8% through LLE. However, clay-alginate-IL beads indicated a removal efficiency of 71.8 % at optimum conditions (600 ppm initial oil concentration, 70 min contact time, 10 pH, and at room temperature) with an adsorption capacity of 431 mg/g. FTIR analysis confirmed the successful chemical bond interaction of oil with IL and beads. SEM analysis verified that beads have a porous and rough surface which is appropriate for the adsorption of oil onto the bead’s surface. TGA analysis provides the thermal degradation profile of clay-alginate-IL. Moreover, the beads used in the adsorption process were regenerated and used up to 4 cycles.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE