United Arab Emirates University
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GENOMIC AND METABOLIC NETWORK PROPERTIES IN THERMOPHILES AND PSYCHROPHILES COMPARED TO MESOPHILES
Full text linkThermophiles and psychrophiles are extremophilic microorganisms that thrive in harsh conditions. Thermophiles are mostly located in hot springs, prosper in high temperatures. Psychrophiles thrive in extremely cold environments, including polar regions and deep-sea habitats. Although they play a crucial role in biotechnology and environmental research, their mechanisms of adaptation are still not well understood. The main objective of this thesis is to understand the genomic characteristics and metabolic network features in thermophiles and psychrophiles compared to mesophiles. The genomes of 59 species among thermophiles, psychrophiles, and mesophiles were collected from the NCBI database. These genomes were used to analyze their key features such as genome length, CDS counts, and G+C content at both whole-genome and codon-specific levels. Codon usage and amino acid abundance were analyzed, and genome-scale metabolic models were constructed using the ModelSEED platform. Additional analysis included model simulation, evaluation of metabolite production rates, pathway enrichment analysis of unique active reactions, and the generating of a metabolic network for all species. The study suggests that psychrophiles have larger genomes, more genes, larger metabolic networks, less metabolite exchange, and greater growth rates compared to thermophiles. Both groups have specific codon and amino acid preferences where thermophiles favor GC-rich codons, and psychrophiles prefer AT-rich codons. These bioinformatic analysis gives us deeper understanding of thermophiles and psychrophiles adaptation mechanisms, which enables their advanced application in biotechnology for industrial processes that requires stability in either extremely high or low temperatures. They also support biofuel production by leveraging their efficient metabolic networks and offer advanced applications in environmental industries
A DATA-DRIVEN RECOMMENDATION SYSTEM FOR SELECTING THE APPROPRIATE MODE OF LEARNING AND INSTRUCTIONAL TOOLS BASED ON COURSE CHARACTERISTICS
Full text linkThe rapid transformation of educational delivery methods during the COVID-19 pandemic required institutions to transition between online, hybrid, and offline learning approaches, creating both challenges and opportunities for educators and students. While online and hybrid learning modes ensured continuity, their effectiveness across different course types remained uncertain. This thesis addresses this gap by developing a data-driven recommendation framework that predicts Course Learning Outcome (CLO) achievement and recommends the most appropriate learning mode (online, hybrid, or offline) along with instructional tools based on course characteristics.This study analyzed 100 undergraduate and postgraduate courses from the College of Information Technology (CIT) at the United Arab Emirates University (UAEU), offered across 1200 sections, covering academic periods from Fall 2020 to Fall 2023, thereby incorporating both pandemic and post-pandemic instructional transitions. The dataset derived from official course portfolios, captures key attributes such as teaching methodologies, assessment strategies, practical engagement, and CLO achievement trends across three departments: Computer Science & Software Engineering (CSSE), Computer & Network Engineering (CNE), and Information Systems & Security (ISS).A machine learning-based approach was utilized to predict CLO achievement rates, comparing multiple models, including Linear Regression and Random Forest, with Gradient Boosting Regressor emerging as the most effective model. Additionally, a rule-based recommendation system was designed to translate predictive insights into structured instructional strategies, ensuring that courses emphasizing hands-on engagement receive practical learning environments, while theoretical and analytical courses are optimized for hybrid or online settings.The findings of this study offer a structured approach to data-driven academic planning, enabling institutions to align course delivery methods with student learning needs. This study contributes to the growing field of educational data science, illustrating how predictive analytics and recommendation systems can facilitate evidence-based decision-making to improve learning effectiveness, instructional design, and curriculum planning in higher education
WIDE LOCK-IN ENERGY HARVESTING FROM VORTEXINDUCED VIBRATIONS OF A DEFORMABLE CYLINDER
Full text linkEnergy harvesting from ambient sources has gained attention due to increasing energy demands. Despite VIV-based harvesters showing significant potential, their lock-in region, where significant power is generated, is narrow. Given the continuously varying ambient conditions of fluid currents, harvesters can easily fall into de-synchronization, yielding low energy output. Existing solutions like tunable masses or multiple degrees of freedom systems increase complexity and weight, limiting practical applications. This work introduces a novel variable diameter cylinder mechanism—a practical technique that actively tunes the cylinder’s geometry in real time to enhance energy harvesting efficiency from VIV. The mechanism employs an expanding pulley system that deforms the elastic circular cylinder radially, dynamically altering its diameter to adjust key non-dimensional parameters governing VIV. This real-time adaptability counteracts ambient fluctuations, significantly widening the lock-in range. The cylinder incorporates a piezoelectric transducer, and the fluid-structure-piezoelectric interaction problem was analyzed numerically to determine the cylinder motion, voltage, and power output. A partitioned Lagrange-Eulerian approach was employed, coupling an FVM fluid solver with a custom-coded structural piezoelectric solver via the preCICE library which enables data mapping and exchange between solvers at run time. The analysis was conducted for different diameter profiles, and the results showed an enhancement in the harvester synchronization width and maximum amplitude by 70% and 117%, respectively, compared to the constant diameter case. Additionally, a 113% increase in peak voltage was achieved, and more than 8 times greater power was generated. The analysis also showed the effect of load resistance on harvesting performance, and the varying diameter cases demonstrated resilience against the shunt-damping effect. The proposed control technique is versatile, as it can be used for VIV suppression as well as energy harvesting applications
الدور العلاجي للببتيدات النشطة بيولوجيًا المشتقة من الهيموغلوبين
Full text linkBioactive peptides are peptide fragments derived from the proteolytic cleavage or maturation of functional proteins that have shown promising therapeutic potential in addressing major health challenges, including type 2 diabetes, hypertension, and pain management. Diabetes is characterized by high blood glucose levels due to insufficient insulin production or utilization. There are several therapeutic targets for managing diabetes, and one key target is dipeptidyl peptidase IV (DPP IV) due to its role in glucose metabolism. In hypertension, angiotensin-converting enzyme 1 (ACE1) is critical for regulating blood pressure by forming angiotensin II, and its inhibition represents an established treatment strategy. Additionally, the δ-opioid receptors (DOR), is involved in modulating pain perception, mood, and neuroprotection, has emerged as a promising target. Bioactive peptides derived from hemoglobin such as hemorphins and hemopressins, have been studied for their ability to interact with DPP IV, ACE1, and DOR using a combination of in vitro enzyme inhibition assays, molecular docking, and extensive molecular dynamics (MD) simulations. The hemorphins exhibit conserved sequences across mammals; however, camel hemorphins harbor a distinct single amino acid variation (Q\u3eR). This study identified hemorphins as potential DPP IV inhibitors, with hemorphin 7 exhibiting the highest binding affinity and stable interactions. These peptides were also evaluated for their interaction with DOR, where camel hemorphin 7 and camel hemorphin 6 showed the highest binding affinity, forming extensive interactions, highlighting their potential for pain regulation. For hypertension, hemopressin variants were tested for ACE1 inhibition. Leucine-substituted hemopressins (Hp-L) demonstrated significantly better inhibition profiles than their phenylalanine-bearing peptides (Hp-F) with RVD-Hp-L exhibited the lowest IC50 value (2.52 ± 0.11 μM). These findings suggest that bioactive peptides derived from hemoglobin are effective natural inhibitors of DPP-IV and ACE1, while acting as agonists of DOR. Future studies should focus on optimizing these peptides for enhanced efficacy and clinical application
نحو مظلة تشريعية إماراتية لإقرار الشخصية القانونية للروبوتات
Full text linkElectronic Monitoring in UAE Criminal Legislation
With the great progress witnessed in the fields of artificial intelligence and robotics, these technologies have had a direct impact on various aspects of daily life. Smart robots, which have the ability to self-learn and make decisions, are no longer mere technical tools, but have become entities that play vital roles in many sectors such as health, industry, security, and government services. How can the relationship between humans and robots be regulated? Is it possible to give robots a legal personality that allows them to bear responsibility for their actions?
The United Arab Emirates is considered a global example in the trust of modern technology, where it has a comprehensive strategy for artificial intelligence aimed at promoting innovation and achieving sustainable development. However, the integration of these technologies requires the existence of legal frameworks commensurate with their complexities, especially as robots evolve into independent entities capable of making decisions. It can affect society positively or negatively.
In this context, the concept of the legal personality of the robot is considered an innovative solution to address a number of issues such as civil responsibility, intellectual property rights, and data protection, and this research focuses on studying the appropriateness of applying this concept within the legal framework of the UAE, taking into account international experiences, and technical and ethical challenges. and the current legislation, while providing practical recommendations aimed at strengthening the position of the UAE as a leading country in the world in the regulation of artificial intelligence and robots.
The aim of this study is to explore the aspects of this topic comprehensively, focusing on how to find a balance between promoting innovation and ensuring the sustainability of social and legal values that contribute to the protection of individuals and society as a whole
PERFORMANCE COMPARISON OF IOT-POWERED INDOOR HYDROPONIC SYSTEMS AND OUTDOOR TRADITIONAL ENVIRONMENT
Full text linkTraditional agriculture faces challenges, including high water consumption, greenhouse gas emissions, and fluctuations in environmental conditions. The research aims to develop alternative sustainable solutions to address issues related to traditional farming. Hydroponics provides opportunities to grow different types of vegetables indoors, where conventional agriculture is challenging. This thesis presents a comparative study of soil-based and hydroponic arugula cultivation using the nutrient film technique (NFT). The proposed methodology focuses on maintaining high similarity in the implementation of components across systems to ensure fair comparison. This thesis utilized distinct approaches. The first approach compared an outdoor soil-based system with an indoor hydroponic system. The second approach compared the indoor NFT system with the outdoor NFT system.
The results demonstrate that outdoor traditional cultivation consumed 68.82% more water than indoor hydroponic cultivation. The mineral plant results indicated that outdoor hydroponic farming produced the healthiest arugula with the most balanced nutrients and the lowest risk of toxicity. The research methodology demonstrates that a three-layer Internet of Things (IoT) architecture is most suitable for hydroponics, particularly in the UAE environment. The components used in this research were sensors, boards, actuators, and wireless Wi-Fi technology. The proposed method minimizes manual monitoring by enabling remote monitoring and control of the two systems through web dashboards and cloud platforms. The sensors collected key environmental parameters such as total dissolved solids (TDS), carbon dioxide (CO2), light intensity, water flow rate, water level, temperature, humidity, and published on cloud platforms. Integrating IoT components with conventional and hydroponic systems enabled real-time monitoring, enhancing crop production, and improving overall cultivation outcomes. Additionally, the integration of Amazon Web Services (AWS) and ThingSpeak clouds has enhanced the system’s performance and provided tools for scalable storage and analysis. Building the NFT system should help farmers to cultivate plants in nutrient-rich water with less human intervention, facilitating sustainable cultivation practices. This comparative study provides valuable insights into the tradeoffs between hydroponic-based arugula cultivation and traditional farming methods
EXPLORING THE QUALITY OF PROFESSIONAL DEVELOPMENT IN ADDRESSING CHALLENGES WITH BEHAVIOR MANAGEMENT OF SPECIAL NEEDS STUDENTS IN INCLUSIVE CLASSROOMS: AN INSTRUMENTAL CASE STUDY
Full text linkInclusive education has become a major educational priority globally and within the United Arab Emirates (UAE), driven by policies promoting the full participation of students with special educational needs (SEN) in inclusive classrooms. This study explores how elementary-level general education teachers perceive the quality of professional development (PD) in addressing their challenges with behavior management of students with SEN in inclusive classrooms. A qualitative case study approach was used, utilizing semi-structured interviews. The findings indicated that teachers face challenges from the behavioral issues of SEN students in inclusive classrooms, affecting both typical peers and teachers. Moreover, teachers had mixed perceptions of PD quality, noting significant advancements in some areas and acknowledging gaps. Many teachers expressed concerns about its overall design, delivery, and limited relevance of the content. The study concludes with evidence-informed implications, grounded in the interview findings, aimed at improving teacher readiness, instructional effectiveness, and outcomes in inclusive classrooms
CONTINUOUS PROFESSIONAL DEVELOPMENT (CPD) FOR INCLUSIVE EDUCATION IN UAE SCHOOLS: CURRENT PRACTICES AND IN-SERVICE TEACHERS PREFERENCES
Full text linkProfessional development serves as a driving force in empowering teachers within inclusive education settings. The purpose of this study was to investigate the perspectives of both general and special education teachers about the effectiveness of currently implemented CPD practices. Data were collected using explanatory mixed-methods design, which included a questionnaire and semi-structured interviews. This method was utilized to improve the depth of research through the integration of quantitative and qualitative data. The combination of these two methods strengthens validity, reduces bias, and increases reliability. Non-probabilistic purposive sampling method was employed to collect the data as a total of 115 teachers from the UAE completed the questionnaire, which was designed to capture their experiences with existing CPD programs. Furthermore, 15 teachers from both general and special education backgrounds were chosen for semi-structured interviews. The findings revealed no statistically significant relationship between demographic variables and CPD efficacy. However, the findings demonstrated that educators had partial satisfaction with the usefulness of current CPD approaches, as well as important hurdles that must be addressed. These barriers included a disconnect between theoretical knowledge and practical application, a lack of collaboration, misalignment between training content and actual classroom challenges, a lack of structured feedback and follow-up, and cultural differences. These challenges affect student outcomes and teacher competencies in managing diverse classrooms and meeting students\u27 needs, which will be reflected in students\u27 progress and social aspect. The recommendations emphasized the need for differentiated and personalized CPD tailored to classroom realities and student needs. Despite fostering improvements to CPD, research on its efficacy in the UAE remains limited. Without ongoing evaluation and investigation, crucial areas for improvement will remain unknown. As a result, the study\u27s findings can help policymakers and educational leaders identify challenges and potential solutions to improve CPD effectiveness and create significant changes in inclusive education. This study strongly advocates for differentiated, practice-oriented CPD with sustained follow-up mechanisms to improve teacher preparedness
AWARENESS AND ATTITUDE TOWARDS CLIMATE CHANGE OF CYCLE 2 AND CYCLE 3 STUDENTS IN AL AIN, UNITED ARAB EMIRATES
Full text linkUnderstanding and addressing climate change is a critical area of knowledge that students must grasp and integrate into their educational journey. This study investigates climate change awareness and attitudes among Cycle 2 and Cycle 3 students in Al Ain, United Arab Emirates. The main purposes of this thesis are to identify the student’s overall level of awareness of climate change, examine their attitudes toward climate change, identify the relationship between students’ awareness and attitudes toward climate change, and assess the impact of student\u27s educational level and gender on their awareness of climate change. The present study uses a mixed methods design involving descriptive exploratory quantitative research and interviews. The quantitative data was collected via a validated questionnaire, and the qualitative data was obtained through semi-structured interviews. Results indicate a moderate level of awareness overall, with Cycle 3 students exhibiting significantly higher awareness than Cycle 2 students. Attitudes toward climate change were positively correlated with awareness, especially among Cycle 2 students. Additionally, the educational level significantly influenced awareness, while gender showed no significant impact. This study contributes to the growing body of research on climate change education by providing insights into students\u27 awareness and attitudes toward climate change. Specifically, this study fills a gap in the literature on climate change awareness and attitudes in the United Arab Emirates, a context with limited prior research
RESPONSIVENESS OF DESERT PLANT DEHYDRIN GENES IN THE ALLEVIATION OF ABIOTIC STRESSES
Full text linkDehydrins (DHNs) are hydrophilic, glycine-rich proteins that accumulate in vegetative tissues of plants in response to abiotic stress and during the late stages of seed maturation. In desert plants, these proteins likely contribute to their specialized adaptation under extreme environmental conditions. To examine the genetic mechanisms underlying DHN associated abiotic stress tolerance in desert plants, this study aimed to isolate them and investigate the architectural features and functional mechanisms related to them. It involved cloning of full-length cDNA sequences of DHN encoding genes, PcDHN1, CcDHN1, PdDHN1, and PdDHN2, from three desert plants Prosopis cineraria, Citrulus colocynthis, and Phoenix datcylifera, followed by bioinformatic analysis and structural modeling. Functional characterization included heterologous expression of these DHNs into yeast mutants and Arabidopsis plants to study their role in heat, salinity, and dehydration tolerance. Recombinant DHN proteins were further produced to examine their protective effects on enzymes, lactate dehydrogenase (LDH) and β-glucosidase (bglG), and Bt biopesticide formulations under adverse conditions. Through sequence analysis, it was found that PcDHN1 and CcDHN1 belonged to Y2SK2 and Y3SK-type DHNs, respectively, whereas PdDHN1 and PdDHN2 were FSK3-type. The four DHN proteins exhibited high hydrophilicity, as indicated by GRAVY scores of less than 0. Structural modeling predicted the presence of wide disordered regions in the DHNs, with random coils and short segments of α-helix constituting a major portion of their structure. In yeast knockout mutants (Cdc25 and AXT3K), the DHNs expression significantly enhanced their tolerance to heat and salinity stress. DHN transformed AXT3K yeast cells showed a selective accumulation of K+ with an increase of 54.28% to 66.64% and decline in Na+ content by 44.96% to 50.67% under saline conditions, providing a 4-fold increase in K+/Na+ ratio. The generated transgenic Arabidopsis lines for dehydration stress tolerance exhibited significantly high proline content and reduced accumulation of reactive oxygen species (ROS), specifically hydrogen peroxide (H₂O₂) and the superoxide radical (O₂⁻), which was associated with an increase of 2-fold in the activity of the antioxidant enzyme system. The overexpression of DHNs in Arabidopsis also enhanced the expression of stress-responsive genes such as RD29A, RD29B, NCED3, and HVA22D that improved their adaptation. Furthermore, these DHN proteins effectively preserved LDH function by a 3- to 4-folds under heat stress, dehydration-rehydration cycles, and freeze thaw treatments, preventing about 20% to 70% of LDH aggregation. While for bglG, it enhanced and protected around 2- to 7-folds of its activity under the heat stress condition. Moreover, the δ- endotoxin Bt formulation complemented with purified DHN proteins showed enhanced efficacy in controlling red palm weevils (RPWs), decreasing their egg hatching by 43.54% to 61.38%, and increasing the larval and adult mortality rates by 2-fold under high temperature stress. Thus, the present study interpreted the potential ability of DHNs to alleviate abiotic stress and protect biomolecules under adverse conditions