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The World Around Us: A First Book Of Discovery
No full textThis book is meant for 3 year olds. It’s about the environment around us. From the sky, to the ground, to the living creatures around us
Facile Synthesis of Zinc-oxide/Silica Aerogel and Their Application in Water Remediation
No full textHighly porous zinc-oxide/silica aerogels and xerogels were prepared via a one-pot sol-gel process at room temperature using propylene oxide as the gelation initiator. For aerogel preparation, the solvent was extracted with supercritical carbon dioxide, while for xerogel preparation, ambient evaporation was performed. The structure and surface properties of the obtained materials have been investigated via a broad range of structural, textural, and morphological characterization before and after calcination. The aerogels and xerogels have a high surface area of 192 and 105 m²/g, respectively, and an open pore structure of 0.7 and 0.2 cm³/g, which enable an effective adsorption-desorption process. The zinc-to-silica molar ratios are stoichiometric, closely matching those of the initial solution.
Zinc oxide-based materials are well known to have a wide range of applications in adsorption processes. To evaluate the capacity of the aerogels and xerogels to absorb dyes, methylene blue (MB) and Congo red (CR) were selected as model compounds, as they exhibit different electronegativities, and a series of batch adsorption experiments were performed at ambient temperature. Both aerogels and xerogels exhibited a high adsorption capacity for both MB and CR dyes, with maximum adsorption capacities of up to 72 mg/g and 58 mg/g, respectively, in 30 minutes. Among the evaluated isotherms, equilibrium data was found to best fit the Langmuir model based on a higher value of the coefficient R² = 0.999. The adsorption process follows pseudo-second-order kinetics
Exploring Gig Work and the Link to Well-Being
No full textProject. M.H.R.M. American University of Beirut. Suliman S. Olayan School of Business, 2025.Gig work witnessed a rapid growth in recent years and increased in interest to researchers. Current research of gig work and its impact on worker well-being is not well understood, which highlights the need for research to synthesize the existing literature on gig work and worker well-being. Specifically, this project identified the need for research to map, synthesize, analyze, and report themes on gig work and its impact on workers’ well-being. This semi-systematic literature review of gig work literature addresses this gap by focusing on gig work - as labor contracted and compensated on a short‑term basis through an external labor market - and well-being, capturing both momentary emotions and longer‑term psychological health. By conducting a semi-systematic review of 118 articles published up to 2024, this project revealed that gig work impacts the well-being of workers through a complex interaction of multiple factors - individual, social, organizational, societal - that have both positive impacts on workers as well as negative ones. Based on these findings the author proposes a series of contributions to practice and research. Thus, this thesis serves as a foundation to drive the literature on gig work by providing a comprehensive view of the factors impacting the well-being of workers
Mapping the Informal Bus System of Greater Beirut and Quantifying Accessibility to Hospitals
No full textThis thesis examines the role of the informal bus system in facilitating access to critical
facilities for lower- and middle-income residents in the Greater Beirut Area (GBA),
Lebanon. By quantifying the relative level of accessibility to hospitals, secured through
the informal bus system, the study evaluates spatial variations across residential areas in
GBA and unravels spatial inequalities in healthcare access in an urban environment
largely shaped by informal mobility systems.
The research methodology draws on approaches developed for Nairobi’s matatu
network and Bogotá’s informal transit to map the informal bus system in the GBA and
generate a General Transit Feed Specification (GTFS) dataset. Accessibility levels to
hospitals were then quantified using the Accessibility Toolbox in ArcGIS. Two
accessibility measures—cumulative opportunities and gravity-based—were quantified
across different travel time cutoffs (30 and 60 minutes), using a network combining bus
and walking.
Results show that hospital accessibility varies significantly based on location, land price
classification, and municipal boundaries. Peripheral zones exhibited limited or no
access via the bus, while Municipal Beirut and immediately contiguous municipal
districts recorded high accessibility levels, ranging between 25 and 34 hospitals
reachable within 30 minutes. Moreover, the study found that while the informal bus
system is generally adequate for providing access in non-emergency situations in
peripheral municipalities, it provides limited accessibility in emergencies when a
hospital needs to be reached in less than 30 minutes.
The findings reveal substantial spatial inequalities in healthcare access across Beirut’s
capital city and point to needed improvement in transport options, particularly in
underserved areas
Development of a Biomimetic Breast Cancer Tissue Model Utilizing Electrospun Scaffolds and a Co-Culturing System
No full textBreast cancer is the most prevalent cancer among women worldwide, with studies
projecting a 40% increase in incidence by 2040. Two-dimensional (2D) cell culture
models have been widely in cancer research. However, these cancer models are often
unreliable as they do not recapitulate the native 3D microenvironment, including critical
cell-cell and cell-matrix interactions. This study presents a 3D breast cancer tissue
model using human hormone-receptor positive breast cancer cell line (MCF-7) and
triple-negative breast cancer cell line (MDA-MB-231), cultured on electrospun
polycaprolactone (PCL) scaffolds to mimic ductal carcinoma in situ.
PCL electrospun scaffolds were fabricated using a 1:1 ratio of dimethylformamide
(DMF) and tetrahydrofuran (THF) solution. The electrospun fibers were then
characterized using a scanning electron microscope for average fiber diameter
measurement. The biological and mechanical properties of the electrospun scaffolds
were optimized for cell culture to evaluate their ability to support cell proliferation. For
this purpose, different concentrations of PCL ranging from 7 to 15 w/v% (7, 8, 10, 12.5,
and 15) were tested. At low concentrations (7 and 8 w/v%), bead defects were observed
in the fibers. Therefore, 10, 12.5, and 15 w/v% were selected to examine the effect of
fiber diameter on cellular growth. The optimal cell seeding density required to achieve
maximum cell coverage in the electrospun scaffolds was assessed for MCF-7 and
MDA-MB-231 cells. It was found that a 15 w/v% PCL solution, with a 30-minute
electrospinning duration, and 5x 106 cell/mL seeding density resulted in the highest cell
coverage of 90% by day 4 of culture for both cell lines. Two scaffold types of 15w/v%
concentration, duct and membrane, were fabricated, and cell growth was assessed from
day 1 to day 4. MCF-7 cells grew better on the membrane than on the ductal model,
with significant growth detected between days 1 and 3, and between days 1 and 4 on
both scaffolds (p<0.05). MDA-MB-231 cells, known for their invasive nature,
proliferated rapidly, reaching a 90% area coverage by day 4 of culture on the membrane
and by day 7 on the duct. In addition, the effect of collagen type I coating on the duct
was investigated with the aim to enhance MCF-7 proliferation. By day four of culture,
MCF-7 cells exhibited a significant increase in cell proliferation in coated versus
uncoated ducts (p<0.01).
The electrospun scaffolds proved to be a suitable scaffold for cell attachment and
proliferation for both cell lines. Normal breast cells (MCF10A) cells will be cultured on3
the scaffolds and then co-cultured with malignant breast cells (MCF-7 or MDA-MB-
231) to replicate the in vivo tumor complexity. The proposed 3D biomimetic co-culture
tumor model is expected to closely resemble the in vivo representation of breast cancer
compared to existing models, thus enabling more effective drug screening and
advancing both basic and applied breast cancer research
Into the wild
No full textA thrilling learning adventure that blends the wonders of technology with a camping journey. This story teaches young children valuable lessons in our tech-driven world.This story follows a group of seventh-grade students on an exciting camping trip guided by their teacher and assistant. What begins as a fun and educational adventure takes an unexpected turn when three students got lost. As the remaining students navigates unexpected challenges to find them, they learn a valuable lesson
Exploring the Versatility of Cyanuric Chloride: Synthesis, Characterization, and Potential Applications of Triazine Based Derivatives
No full textOrganic chemistry plays a transformative role in the medical field, where the
development of new molecules and innovative approaches has driven progress in drug
discovery and disease treatment. As researchers continually seek novel therapeutic
agents, compounds with unique structural properties and dynamic functionality are of
high interest. Cyanuric chloride, a triazine-based reagent, stands out in this regard. Its
stability and electrophilic nature, which allow sequential substitution by various
nucleophiles, make it well-suited for diverse synthetic applications. Previous work in this
research group developed novel triazine-based compounds that show promising effects
in suppressing the progression of Diabetic Nephropathy (DN). This has motivated the
synthesis of analogues with greater tunability for enhanced clinical activity. Herein,
cyanuric chloride is utilized as a core reagent for nucleophilic substitutions. Pyrimidines - Uracil, thymine, and cytosine-propanehydrazides, chosen for their role as nucleic bases
naturally present in the human body, are introduced to functionalize the cyanuric chloride,
thereby creating compounds with potentially improved biocompatibility. Additionally,
tert-butyl carbazate is used as a versatile substrate, allowing further functionalization of
the synthesized molecule, enhancing its potential for post-synthetic modifications and
adaptability for more targeted interventions. The choice of nucleophiles, together with
the multifunctional capability, enables the synthesis of structurally diverse and
biologically significant molecules. By integrating these components, in this research we
aim to synthesize novel molecules that incorporate the robust framework of cyanuric
chloride with nucleic base derivatives and tert-butyl carbazate. Structural characterization
using Nuclear Magnetic Resonance (NMR), Fourier-Transform Infrared Spectroscopy
(FTIR), and ThermoGravimetric Analysis (TGA), confirms the identity and purity of the
synthesized molecules. Given the structural and functional properties of the synthesized
molecules, they hold promise for applications in the treatment or management of diseases,
with potential impacts in areas such as diabetes and cancer. This study thus contributes
to the ongoing exploration of cyanuric chloride derivatives in medicinal chemistry,
offering insights into their structural versatility and applicability in designing new
pharmaceutical compounds
An Optimized Approach Towards Fabricating Microfiltration Membranes from Recycled Discarded Fishing Nets
No full textDiscarded fishing nets, predominantly composed of polyamide-6 (PA6), are a major
source of marine microplastic pollution and represent an untapped resource of high
performance engineering polymers. This study presents a sustainable upcycling
approach that repurposes this waste material into functional microfiltration membranes
for environmental remediation. Membranes were fabricated via the non-solvent-induced
phase separation (NIPS) method using PA6 concentrations ranging from 8–14 wt.% and
gelation times between 0–10 minutes, yielding tunable structures. Scanning electron
microscopy (SEM) revealed that higher polymer concentrations led to denser membrane
architectures, while intermediate gelation times (6–8 minutes) produced the smallest
and most uniform pores. Filtration tests demonstrated the membranes' ability
to completely remove microplastics ≥400 nm, with hydrodynamic flux closely
correlated to pore size, porosity, wettability, and membrane thickness. These findings
highlight the potential of recycled PA6 membranes as an environmentally responsible
and cost-effective solution for microplastic removal, transforming plastic waste into a
tool for combating plastic pollution
Tic by Tic: Different, Not Less
No full textThis book talks about a young boy called Rami who has Tourette's syndrome. He was bullied at school, until a fellow peer came to his rescue
Defense Mechanisms for Mitigating Adversarial Attacks Against Deep Learning-Based Traffic Signs Recognition of Autonomous Driving Cars
No full textArtificial Intelligence (AI) techniques, particularly machine learning and deep learning, have gained significant attention for their ability to solve complex problems. Among these, Deep Neural Networks (DNNs) have demonstrated remarkable success in handling nonlinear problems due to their capacity to process vast amounts of data during training. However, the widespread deployment of DNNs in critical applications has raised concerns regarding their security and robustness. Notably, DNNs are vulnerable to adversarial attacks—carefully crafted perturbations that manipulate input data to deceive the model into making incorrect predictions.
One of the most critical applications of DNNs is in autonomous vehicle systems, which rely on deep learning models for tasks such as object detection, localization, navigation, and trajectory planning. Despite their effectiveness, adversarial attacks on these models can lead to erroneous decisions with potentially catastrophic consequences. In particular, compromising the traffic sign recognition system of an autonomous vehicle can severely impact its decision-making process, posing serious safety risks.
This dissertation proposes three novel defense mechanisms to mitigate adversarial attacks on DNN-based traffic sign recognition systems in autonomous vehicles. The first approach enhances input robustness by augmenting acquired data with descriptive metadata, including a segmented and an inverted version of the input. Beside the main model, another model called a verifier is employed. By comparing predictions across multiple versions of the inputs, this method effectively detects adversarial manipulations. The second approach applies image transformations, such as splitting and flipping, to disrupt adversarial perturbations while preserving the integrity of clean inputs. The third defense mechanism leverages Siamese Neural Networks for similarity learning. Unlike traditional applications of Siamese Networks for object recognition, this work utilizes them for adversarial detection. The main model predicts a class to the input, then two random clean samples are drawn from the same class for similarity comparison with the input. The Siamese embedding representations of the input and the random samples are compared using the cosine similarity measure. If the input deviates significantly in feature space, it is flagged as adversarial.
Additionally, to enhance detection performance across various attack types, all proposed methods incorporate anomaly detection using a One-Class Support Vector Machine (OC-SVM). By exploring diverse defense strategies, this research aims to develop robust and generalizable mechanisms to secure DNN-based traffic sign recognition systems in autonomous vehicles, as well as other critical AI-driven applications, against adversarial threats