AUB ScholarWorks (American Univ. of Beirut)
Not a member yet
33634 research outputs found
Sort by
Agroecology Knowledge and Practices in Early Modern Levantive Agriculture: Exploring Abdul Ghani Al Nabulsi’s Book “Ilm El-Milaha Fi Ilm El-Filaha”
No full textThis Thesis explores the agroecological knowledge from the Levantine early modern period as a source of indigenous knowledge that could be adapted to the modern world. The research uses principally the work of Abdul Ghani Al Nabulsi as a source. Al Nabulsi is a polymath who lived between the 17th and 18th century and died in Damascus in 1731, and gathered a wealth of agroecological, and agricultural practices and knowledge occurred during his lifetime and before from ancient and current sources.
This study evaluates traditional Levantine farming methods and their potential applications in modern agroecological practices using historical analysis and scientific research. Indigenous knowledge from the early modern Levant is compared to modern agricultural practices and insights from Africa and Latin America to demonstrate the resilience, adaptability, sustainability, and wealth of these traditional practices.
The research employs an interdisciplinary approach to analyze Al Nabulsi’s book, involving a critical examination of its content, comparison with recent scholarly works, and a detailed look at the historical context. The findings suggest that traditional agricultural practices promote sustainable and efficient agroecological practices that tackle the challenges of contemporary cultivation.
Furthermore, combining these traditional methods with modern agroecological principles can improve food security, reduce environmental impact, enhance ecosystem health, and promote sustainable agricultural practices. This approach highlights the importance of preserving cultural heritage and using indigenous knowledge to inform modern agroecological practices.
The study's findings can help develop sustainable agricultural policies, enhance local farming practices, preserve cultural heritage, and support social-base development programs
A 1D Model to Study Nuclear Reactions in Fusion Devices
No full textThe main objective of nuclear fusion is the generation of a tremendous amount
of energy by merging light atomic nuclei, particularly Hydrogen isotopes, namely
deuterium, and tritium, to form heavier Helium while releasing a fast neutron and
energy. The existence of fast neutrons complicates the choices of the materials
and presents technological challenges. On the other hand, the reaction with only
deuterium requires more energy but produces slow neutrons, which can be stopped
by a relatively simple shield.
Our study is the first of its kind at AUB. First, we obtain the set of equations that
describe the power and particle balances in a D–T and D-D fusion plasmas operating
under fusion “burning” plasma conditions. We investigate the sources and sinks of all
the species in the plasma that contribute to the particle and energy balance. Next,
we analyze the cross-sections for the D-D and D-T fusion reactions, followed by the
heat exchange mechanisms among the different particles. The particle and energy
confinement times will be obtained analytically and included in the conservation
equations. We also include the effects of plasma-wall interactions by discussing the
recycling and sputtering processes in the fusion device.
After all the terms are identified, we build a code to solve the equations of
this complex system as a function of time. This is followed by benchmarking our
code. To this end, we use the parameters of the EAST Tokamak. We were able
to recover the main plasma parameters with reasonable values of the particle and
energy confinement times. However, the times obtained are relatively far from those
predicted by the scaling laws.
We then turn toward the ITER tokamak to simulate the expected plasma properties under a variety of conditions. The plasma properties of ITER are used, and
we change the auxiliary power, the plasma current, and the confinement time and
study their effects mainly on the plasma density and temperatures
Synthesis and Optimization of Iron and Manganese Oxide Nanoparticles for Environmental Applications
No full textHematite, maghemite, and hausmannite play significant roles in various technological and environmental applications due to their distinct properties. Hematite is valued for its excellent adsorption capabilities, suitable bandgap for solar applications, and versatility in sensors and environmental remediation, while maghemite’s unique magnetic properties make it indispensable in superparamagnetic applications, drug delivery, and imaging. Additionally, manganese oxide (Mn₃O₄) stands out for its catalytic efficiency, affordability, and biocompatibility, making it a promising material for both catalytic processes and biomedical applications. Hematite (α-Fe₂O₃), maghemite (γ-Fe2O3) and hausmannite (Mn₃O₄) nanoparticles were synthesized via the chemical coprecipitation method; a technique favored for its cost-effectiveness, simplicity, and scalability. A systematic optimization study of key synthesis parameters, including precursor ratios, reaction temperature, synthesis time, and surfactant use, was done to produce nanoparticles with uniform morphology, high crystallinity, and excellent thermal stability. The optimized factors for the synthesis of metal oxide polymorphs were utilized in environmental remediation of water from azo dyes (Congo Red and Methylene Blue). The previous parameters were varied and quantified along with their effects using several microscopic and spectroscopic techniques, such as thermogravimetric technique, X-Ray diffraction, Scanning electron microscopy and UV-vis spectroscopy
Readiness and Perceptions of High School Teachers towards AI in Education: A Case Study in Jeddah Private Schools
No full textProject. M.A. American University of Beirut. Department of Education, 2025.The integration of artificial intelligence (AI) in any field is gaining traction, including the education sector (Celik, 2022). However, the potential of AI in education has not been fully realized yet (Luckin et al., 2022; Celik 2022). Seufert et al. (2021) claimed that one main reason for that is overlooking teachers’ role and readiness to integrate AI into their teaching practices.
Several studies addressed the growing interest in the topic of acknowledging teachers’ perceptions regarding artificial intelligence in education (AIEd) (Cabero-Almenara et al., 2024). This study aims to explore teachers’ perceptions of integrating educational AI- based tools, with a particular focus on their readiness to utilize these technologies in their teaching practices and to support the achievement of learning outcomes. To address these objectives, a mixed approach is adopted. A survey is used to gather quantitative and qualitative data from high school teachers across grades nine to twelve in two private schools in Jeddah, Saudi Arabia.
The frequency distribution of participants’ beliefs and perceptions is presented. The findings of this study help identify gaps in teachers’ knowledge and readiness, as well as the perceived benefits and barriers in integrating AI. These insights highlight the need for better training and support to ensure the responsible and effective implementation of AI in schools
Monge-Ampère Equation and Its Numerical Analysis
No full textIn this study, we focus on the Monge-Amp` ere equation and its applications in non
linear partial differential equations (PDEs). The work extends upon existing math
ematical frameworks to include the derivation of the Monge-Amp`ere equation and
its numerical solution. Employing a rigorous analytical approach, the derivation
highlights the intrinsic geometric and variational principles underlying the equa
tion. Furthermore, in the numerical solution, we use finite element techniques,
implementing them to solve the Monge-Amp` ere equation efficiently using FEniCS
Effect of Magnetic Field and Titanium Oxide Nanoparticle on the Mechanical Properties of Concrete
No full textThis research explores the novel application of magnetic fields in conjunction with Titanium Oxide (TiO2) nanoparticles to enhance the mechanical properties of concrete, presenting a transformative approach in concrete technology. By investigating this innovative synergy, the study aims to reduce cement content—an unprecedented step towards minimizing the carbon footprint—while simultaneously improving concrete strength. The potential scientific contribution lies in pioneering a method that not only boosts performance but significantly lowers greenhouse gas emissions, offering a
sustainable alternative to traditional concrete production techniques.
The present experimental study investigates the influence of magnetic field intensity, exposure duration, and titanium dioxide (TiO2) nanoparticle fraction on the compressive strength and microstructural behavior of concrete with reduced cement content. Concrete mixes with a 10% reduction in cement content were prepared with TiO2 nanoparticle additions of 0.5%, 2%, and 4% by weight of cement. These mixes were subjected to a uniform magnetic field treatment at induced voltages of 25 V and 80 V, generating maximum magnetic flux densities of approximately 270 mT and 450 mT, respectively. The treatments were applied for 2 and 5 minutes, in both the fresh and hardened states of the concrete. Mechanical behavior was evaluated through compressive strength tests at 7 and 28 days, accompanied by scanning electron microscopy (SEM) analysis to assess microstructural changes. Results revealed that incorporating 4% TiO2 nanoparticles alone significantly compensated for the reduced cement content, achieving a compressive strength increase up to 17.7% at 7 days and 7.42% at 28 days compared to the control sample. Magnetic field application further improved mechanical properties, with maximum strength enhancements reaching approximately 32% at 7 days and 22% at 28 days for specimens treated at optimal conditions (25 V for 5 minutes). SEM analysis confirmed that applying magnetic fields improved nanoparticle dispersion, accelerated cement hydration, increased calcium silicate hydrate (C-S-H) gel density, and reduced porosity, leading to a denser and more cohesive microstructure. However, higher magnetic intensities (at 450 mt ) induced overheating, causing micro-cracking and limiting mechanical benefits. Fresh-state magnetic exposure yielded superior early-age strength gains at medium-to-high nanoparticle concentrations, while hardened-state exposure provided sustained long-term benefits at lower concentrations. The findings suggest a promising strategy for enhancing concrete properties through controlled magnetic field treatment and nanoparticle incorporation, potentially reducing cement content, and thus the carbon footprint, without compromising structural integrity—an area not comprehensively explored previously
Noonoo's Tasty Travels
No full textA children's book, created by AUB students from the Education Department, for the course EDUC218 as a final project.Noonoo’s Tasty Travels is an exciting rhyming adventure for little foodies ages 2–4! Follow Noonoo, a fluffy dog with a big love for food, as he trots around the world to try new dishes, make friends, and discover fun cultural traditions, one yummy bite at a time
Reflections on the Symposium on the Teaching of Writing in Lebanon: An Interview with Malakeh R. Khoury
No full textMENA Writing Studies, vol. 1.1, Spring 2025, pp. 84-111.Includes bibliographical references (pages 98-100)Appendices: pages 100-111.The aim of this article is to document and critically reflect upon the significance of
a symposium for teachers of writing in English language medium universities in
Lebanon that took place annually over the period of 2013-2019. To gain knowledge
of this event, two of the authors conducted an interview with the symposium’s cocreator and main organizer, Malakeh R. Khoury, and contextualized it in reflective
discussions of local conditions. The article frames the symposium as a key
national-level event in the local community of practice that responds to the need to
organize local teachers of writing in the absence of other relevant channels of
communication and exchange of expertise
Intelligent Systems for Detection and Classification of Sleep Apnea
No full textClassical machine learning has extensively been used to treat bio-signals to detect and classify multiple diseases, and this approach has also extended to deep learning,
offering more sophisticated and accurate methods for analyzing complex physiological
data.
Photoplethysmography (PPG) offers a non-invasive method to study blood volume
changes in the vascular system. It transmits light through the skin into the vascular beds
and measures the changes in the intensity of the transmitted or reflected light caused by
blood volume changes, providing insights into cardiovascular functions. This method
has been shown to return a high-fidelity signal regarding heart rate and blood pressure,
making it a reliable and convenient way to study cardiovascular function and potentially
monitor diseases such as sleep apnea.
However, PPG measurement suffers from variability based on the location of
measurement, skin tone, and motion artifacts, which can lead to inaccurate readings.
This study investigates the impact of sensor location on photoplethysmography (PPG)
signal quality for sleep apnea detection.
Firstly, we plan to demonstrate how the signal varies depending on the properties of
different recording sites based on other factors such as skin thickness and vascular
density.
The feasibility of classifying apneic events as obstructive or central using only PPG
signals is examined PPG by designing intelligent systems to do so. We will then design
a flowchart that will utilize a combination of PPG signals, deep learning models and
algorithms, to differentiate between the two types of apneas based on the distinct
physiological markers.
Our approach seeks to enhance the accuracy and reliability of sleep apnea diagnosis and
classification, for a better diagnosis of sleep apnea while using minimal commonly used
wearable devices
pictures from public domain images
No full texta prince who defeats the not so evil dragon by using kindness and care. This fairytale uses a non realistic setting and characters to provide a deeper message to its audience about real life situations