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Corrections to Yukawa couplings from higher dimensional operators in a natural SUSY SO(10) and HL-LHC implications
No full textWe consider a class of unified models based on the gauge group SO(10) which with appropriate choice of Higgs representations generate in a natural way a pair of light Higgs doublets needed to accomplish electroweak symmetry breaking. In this class of models higher dimensional operators of the form matter-matter-Higgs-Higgs in the superpotential after spontaneous breaking of the GUT symmetry generate contributions to Yukawa couplings which are comparable to the ones from cubic interactions. Specifically we consider an SO(10) model with a sector consisting of 126 + 126 + 210 of heavy Higgs which breaks the GUT symmetry down to the standard model gauge group and a sector consisting of 2 × 10 + 120 of light Higgs fields. In this model we compute the corrections from the quartic interactions to the Yukawa couplings for the top and the bottom quarks and for the tau lepton. It is then shown that inclusion of these corrections to the GUT scale Yukawas allows for consistency of the top, bottom and tau masses with experiment for low tan β with a value as low as tan β of 5–10. We compute the sparticle spectrum for a set of benchmarks and find that satisfaction of the relic density is achieved via a compressed spectrum and coannihilation and three sets of coannihilations appear: chargino-neutralino, stop-neutralino and stau-neutralino. We investigate the chargino-neutralino coannihilation in detail for the possibility of observation of the light chargino at the high luminosity LHC (HL-LHC) and at the high energy LHC (HE-LHC) which is a possible future 27 TeV hadron collider. It is shown that all benchmark models but one can be discovered at HL-LHC and all would be discoverable at HE-LHC. The ones discoverable at both machines require a much shorter time scale and a lower integrated luminosity at HE-LHC
A Roadmap for Policy-Relevant Sea-Level Rise Research in the United Arab Emirates
No full textThe United Arab Emirates (UAE) has a long-term policy horizon, the financial capital, and a vision for a sustainable knowledge-based economy. These characteristics uniquely situate it as a potential leader for sea-level rise research. Climate science is already growing, and at the center of the UAE's pivot toward climate research is a burgeoning concern for sea-level rise. Over 85% of the UAE's population and more than 90% of the nation's infrastructure is within a few meters of present-day sea-level. With its low-lying and shallow-sloping geography (about 35 cm per km), this high-value coastline, including the rapidly expanding cities of Dubai and Abu Dhabi, is particularly vulnerable to sea-level rise. Meanwhile, limited regional research and data scarcity create deep uncertainty for sea-level projections. We set out a potential roadmap for the UAE to capitalize on its strengths to create usable and relevant sea-level projections for the region. With a newly established Climate Change Research Network, the UAE government is beginning to draw together universities and research centers for “furthering effective data collection and management, and advancing policy-relevant research on climate impacts and adaptation1.” By consolidating ideas from the science community within the UAE, we identify promoters and barriers to data gathering, information sharing, science-policy communication, and funding access. Our paper proposes pathways forward for the UAE to integrate sea-level science with coastal development and form best practices that can be scaled across climate science and throughout the region.Center for global Sea Level Change (CSLC) of NYU Abu Dhabi Research InstituteNYU Abu Dhabi Water Research Center gran
Objectively quantified physical activity and sedentary behaviour in a young UAE population
No full textObjectives There is a lack of public awareness of the importance of engaging in physical activity (PA) in the United Arab Emirates (UAE). Nearly 58% of the UAE adult population self-reports as being physically inactive although little accelerometer data currently exists. The aim of this study was to obtain the first dataset that objectively quantifies PA and sedentary behaviour (SB) in young UAE adults. Methods This cross-sectional study recruited 140 university students. Body composition and accelerometry was assessed using a Tanita body composition analyser and ActiGraph accelerometer. Differences (p≤0.05) between gender (male vs female) and body mass index (normal vs overweight/obese) were determined using independent samples t-tests and χ² tests for nominal variables. Results Both males and females spent high amounts of time in SB, encompassing ~80% of waking hours. PA was primarily light intensity (14.1%), although males spent significantly greater time in moderate-to-vigorous intensity activity. Moreover, 50% of males compared with 76.6% of females were classified as sedentary/low active according to daily step counts. Conclusion Our data provide evidence of high levels of SB among young adults in the UAE with PA being predominantly light intensity, therefore, both PA and SB should be carefully monitored in this country.American University of Sharja
Machine Learning-Based Approach for EV Charging Behavior
No full textA Master of Science thesis in Computer Engineering by Sakib Shahriar entitled, “Machine Learning-Based Approach for EV Charging Behavior”, submitted in April 2021. Thesis advisor is Dr. Abdulrahman Al-Ali and thesis co-advisor is Dr. Ahmed Osman-Ahmed. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).As smart city applications are moving from conceptual models to the development phase, smart transportation, of smart cities’ applications, is gaining ground nowadays. Electric vehicles (EVs) are considered to be one of the major pillars of smart transportation. EVs are ever-growing in popularity due to their potential contribution in reducing dependency on fossil fuels and greenhouse gas emissions. However, large-scale deployment of EV charging stations poses multiple challenges to the power grid and public infrastructure. The solution to this problem lies in the utilization of scheduling algorithms to better manage the growing public charging demand. Modeling EV charging behavior using data-driven tools and machine learning algorithms can improve scheduling algorithms. Researchers have focused on using historical charging data for predictions of behaviors such as departure time and energy needs. However, variables such as weather, traffic, and nearby events, which have been neglected to a large extent, can perhaps add meaningful representations, and provide more accurate predictions. Therefore, in this thesis we propose the usage of historical charging data in conjunction with the weather, traffic, and events data to predict EV departure time and energy consumption. Several popular machine learning algorithms including random forest, support vector machine, XGBoost, and deep neural networks are investigated. The best predictive performance is achieved by an ensemble-learning model, which improves upon the existing works in the literature with SMAPES of 9.9% and 11.6% for session duration and energy consumptions, respectively. In both predictions, we demonstrate a significant improvement compared to previous work on the same dataset and we highlight the importance of traffic and weather information for charging behavior predictions.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Synthesis and low-order optical nonlinearities of colloidal HgSe quantum dots in the visible and near infrared ranges
No full textWe synthesize colloidal HgSe quantum dots and characterize their nonlinear refraction and nonlinear absorption using a Nd:YAG laser and its second harmonic. The 7.5 nm quantum dots were synthesized using the hot-injection method. The nonlinear absorption (β = 9×10ˉ⁷ cm Wˉ¹) and negative nonlinear refraction (γ = -5×10ˉ¹² cm² Wˉ¹) coefficients of colloidal quantum dots were determined using the 10 ns, 532 nm laser radiation. The joint influence of above processes was realized at a higher intensity of probe pulses. In the case of 10 ns, 1064 nm radiation, only negative nonlinear refraction dominated during z-scans of these quantum dots. The studies of optical limiting using two laser sources demonstrated the effectiveness of this process at 532 nm. The role of nonlinear scattering is analyzed. We discuss the mechanisms responsible for the nonlinear refraction processes in colloidal HgSe quantum dots.Russian Foundation for Basic ResearcState Assignment to Higher Educational Institutions of Russian FederationEuropean Regional Development Fun
Surveilling and Spying on Romantic Partners in the United States: The Influence of Perceived Maternal Rejection and Psychological Maladjustment
No full textAccording to interpersonal acceptance-rejection theory (IPARTheory), people who perceive rejection by important others experience more psychological maladjustment than those who do not perceive rejection. IPARTheory predicts universal responses to perceived rejection or acceptance, making it important to explore its predictive ability with theoretically-related constructs like romantic relationships. Participants (N = 443; Mage = 36.05 years; SD = 11.26; 46% identifying as men, 45.4% reported their assigned sex at birth as male) completed surveys regarding perceptions of their childhood relationships with their mother, interpersonal anxiety, engagement in romantic surveillance, jealousy, infidelity, sociosexual orientation, and gender norms. We examined how well perceived maternal acceptance-rejection (independent variable) predicted reasons to spy/stalk on a romantic partner and the likelihood of spying/stalking (dependent variables). For both models, we explored psychological maladjustment, interpersonal anxiety, jealousy, and sociosexuality as mediators and included correlated demographic variables as covariates in the models. Jealousy mediated perceived maternal rejection and increased surveilling. Our study broadens the understanding of variables that influence surveilling behaviors in romantic relationships in the United States, and provides support for the universal application and predictive ability of IPARTheory
Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP
No full textA Master of Science thesis in Electrical Engineering by Nada Abdelhafez entitled, “Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP”, submitted in November 2021. Thesis advisor is Dr. Mohamed S. Hassan and thesis co-advisor is Dr. Taha Landolsi. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Video streaming stands out as the most significant traffic type consumed by mobile devices. This increased demand has been a major driver for research on bitrate adaptation algorithms. Bitrate adaptation ensures high user-perceived quality, which, in turn, correlates with higher profits for content providers and delivery systems. Dynamic Adaptive Streaming over HTTP (DASH) is a widely adopted video streaming standard utilized by service providers to provide competitive Quality of Experience (QoE). It is capable of providing seamless streaming via uncertain network conditions by switching across different video qualities and their corresponding video segment bitrates. The complexity of the video streaming environment makes it a good candidate for different learning-based approaches. Accordingly, this thesis proposes and assesses different learning-based adaptation approaches. The first proposed approach is the hybrid QoE-based algorithm, which manages the trade-off between video quality, re-buffering and quality switching events that impact the user-perceived quality. The objective is to optimize the QoE metric which is constrained by the network throughput, segment size, and buffer occupancy to continuously select the optimum bitrate levels with low complexity. The second proposed approach is the state-of-the-art DQNReg, a reinforcement learning based technique that enhances the classical deep Q-learning method. A segment-wise QoE-based reward function is established so that the learning strategy can converge towards maximizing the QoE outcome. The proposed adaptation approaches have been thoroughly evaluated using trace-based simulation for fixed and mobile networks. The first hybrid QoE-based approach performance surpasses that of the benchmark algorithm and the DQNReg algorithm outperforms other existing methods. The evaluations show that the DQNReg significantly reduces the re-buffering duration while maintaining higher video quality and relatively lower quality variations.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Dual-Targeting and Stimuli-Triggered Liposomal Drug Delivery in Cancer Treatment
No full textThe delivery of chemotherapeutics to solid tumors using smart drug delivery systems (SDDSs) takes advantage of the unique physiology of tumors (i.e., disordered structure, leaky vasculature, abnormal extracellular matrix (ECM), and limited lymphatic drainage) to deliver anti-cancer drugs with reduced systemic side effects. Liposomes are the most promising of such SDDSs and have been well investigated for cancer therapy. To improve the specificity, bioavailability and anti-cancer efficacy of liposomes at the diseased sites, other strategies such as targeting ligands and stimulus-sensitive liposomes have been developed. This review highlights relevant surface functionalization techniques and stimuli-mediated drug release for enhanced delivery of anti-cancer agents at tumor sites, with a special focus on dual functionalization and design of multi-stimuli responsive liposomes.American University of SharjahAl-Jalila FoundationAl Qasimi FoundationPatient's Friends Committee-SharjahBiosciences and Bioengineering Research InstituteDana Gas Endowed Chair for Chemical Engineerin
Optimization of Vapor Compression Refrigeration Cycles with Clathrate Hydrates Thermal Energy Storage
No full textA Master of Science thesis in Mechanical Engineering by Akram Mohamed Gadalla entitled, “Optimization of Vapor Compression Refrigeration Cycles with Clathrate Hydrates Thermal Energy Storage”, submitted in December 2021. Thesis advisor is Dr. Mohamed Omar Abdelgawad. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This thesis presents detailed modelling and analysis of different refrigeration systems as well as cold thermal energy storage systems (CTES) using clathrate hydrates. The Engineering Equation Solver (EES) was used to model various refrigeration systems including liquid line-suction line, dedicated mechanical subcooling, a two-stage with a flash chamber and two evaporators, and with a flash tank and intercooling. The refrigerants used in the modelling analyses include three different categories namely hydrofluorocarbon (HFC) (R134a, R404A, R410A), hydrochlorofluorocarbon (HCFC) (R22, R123, R141b), and chlorofluorocarbon (CFC) (R114, R11, and R12). Performance indicators including energetic and exergetic coefficient of performances (COPs), refrigeration efficiency, compressor power per ton refrigeration, and the exergetic destruction ratio were calculated and compared among proposed refrigeration systems under different operating conditions. Results indicate that R134a had the best performance. It was found that the energetic and exergetic COPs of liquid-line suction line system at the operating evaporator and condenser temperatures of 4ºC and 40ºC are about 5.0 and 0.29, respectively. At the same operating conditions, the refrigeration efficiency, and the input power per ton refrigeration of R134a were found to be 66% and 0.7 kW/ton, respectively. Results of the two-stage with a flash chamber and two evaporators had greatest performance with COP = 7.4 and kW/ton = 0.47. The effect of additives in a high-pressure tube was studied using constant temperature baths to identify the fastest clathrate formation time. Indirect and direct contact CTES using clathrate hydrate was evaluated experimentally with single stage and two stage systems. Numerous closed loop cooling cycles using clathrate hydrates of R134a have been evaluated at different operating conditions such as refrigerant flow rate, compressor speed, and water/refrigerant mass ratio to determine the COP, and the clathrate hydrates behaviour during the charging mode. Experimental results indicate that at higher water/refrigerant mass ratios in the storage tank (evaporator; crystallizer) the COP decreases due to increases in charging time and compressor power input. Finally, experimental results conclude that COPs of CTES systems are higher than COPs of the conventional refrigeration systems used in modelling.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
World Literature in the World? Kahf ’s The Girl in the Tangerine Scarf and the Transnational Reading Public
No full textCriticized for being too Euro- and Americentric, world literature scholarship tends to center on the American implications of this shortcoming, with little discussion of world literature beyond these centers. This paper thus addresses the function of world literature beyond these centers, particularly in the lingua franca of global business: English. Drawing from my experience in the United Arab Emirates, I argue that because students in the region come from places with fraught colonial histories, migrant, Anglophone literature is critical in the world literature classroom because it allows them to see their own experiences articulated in the global literary vernacular. Using Mohja Kahf’s The Girl in the Tangerine Scarf as an example, I show how its transnational scope addresses both the hegemonic, Euro-American gaze, but also the students’. Thus, Anglophone literature is not necessarily the extension of an imperialist project or a flattening of differences; rather, it becomes an articulation of them