Digital Commons Network^™

Utilization Of Biochar From Date Palm For Wastewater Treatment Technologies: Mini-Review, Atheel Alwash, Emad Yousif, Salam Mohammed

Al-Mustaqbal Journal of Sustainability in Engineering Sciences

Recently, recycling agricultural waste has gained great importance in the field of the biochar industry, as it is a sustainable and inexpensive material that can be used to get rid of environmentally polluting materials. Dates are one of the major agricultural wastes in Iraq and the Gulf countries, which include fronds, seeds, and trunks. The challenge of obtaining a green and clean environment is represented by the safe disposal of these residues. These wastes are promising materials for producing biochar products as efficient adsorbents with improved characteristic properties. The present article revises the synthesis of biochar derived from date palm …

A Proposed Urban Branding Strategy As Sustainable Urban Regeneration Policy, A Case Study Of Burj-Al Burullus City, Dalia S. Shebl, Kariman A. Shawky

Mansoura Engineering Journal

This study examines the importance of a branding strategy that can be applied in Burj Al-Burullus city to promote and catalyze cultural heritage branding and invest in these facilities for economic and tourism purposes. By measuring the indicators of how urban branding may be achieved. Burj Al-Burullus city is empirically examined using Identity-Based Approach. Based on profound theoretical and analytical studies, the branding concept was studied and analyzed composing a list of indicators for tangible and intangible elements that illustrate the urban branding value of cities. Followed by an analysis of Burj Al-Burullus city using GIS and city data base …

Towards Computational Methods In Medical Data Analysis: From Speech And Text To Imaging, Kristin Qi

Graduate Doctoral Dissertations

Early detection of cognitive decline and efficient medical image analysis remain critical challenges in healthcare. Traditional clinical assessments are infrequent and resource-intensive, while everyday speech data and unlabeled medical images remain largely unexploited. This dissertation develops computational methods integrating machine learning and artificial intelligence across speech, text, and imaging modalities to address challenges in medical data processing. For cognitive monitoring, this work first introduces methods using voice assistant systems to collect longitudinal speech data in home environments, demonstrating that incorporating historical session patterns significantly enhances detection of mild cognitive impairment. Building on this foundation, a framework combining large language model-driven …

Umwelt, Sujetos Transindividuales E Intencionalidad Compartida: Cuerpo, Significación Y Socialidad En La Construcción Del Conocimiento, Juan C. González Vidal

Journal of Roleplaying Studies and STEAM

En este trabajo abordamos, desde el punto de vista semiótico, el vínculo indisoluble que existe entre el cuerpo humano, la significación y la socialidad. Partimos del postulado de que el cuerpo es, desde el nacimiento, una entidad sintiente; luego, una vez adquirida la capacidad de generar procesos semiósicos primarios, empieza a ordenar y a clasificar los estímulos exteriores, hecho en el que se asienta el fundamento de su orientación básica en el entorno. Conforme aumentan sus competencias semiósicas, se incrementan sus capacidades perceptivas y cognitivas que, al ser afirmadas, lo llevan a alcanzar finalmente los más altos grados de socialidad. …

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 4 [2025], Número 2 (Issue 2), Cristo Leon, Romano Ponce-Díaz Phd, Ivan Avila Gonzalez Phd, James Lipuma Dr., Bruce G. Bukiet, Ricardo Victoria-Uribe, Nazario Robles-Bastida, Chris Birmingham, Ximena Diaz Santillan, Edgar Francisco Vázquez Martínez He, Jorge Prieto Terrones, Juan Carlos C. González Vidal S, Edgar Meritano, Laura Magela Garcés Ramírez

Journal of Roleplaying Studies and STEAM

En una sesión de juego por medio del registro lingüístico se organiza la escena, se orienta la manera de nombrar las tareas, se distribuyen los roles actanciales, se establecen la expectativas; por lo tanto, se establece una puesta en escena. De tal forma, las prácticas lúdicas y ficcionales se configuran a partir de nuestra mirada del mundo e irremediablemente también reconfiguran esa misma mirada. El ser y el estar en un espacio es la especificidad mediática fundamental de los juegos de rol; dicho de otra manera, en los sistemas de juego de rol dentro de sus universos narrativos, en su …

A Digital Twin Framework For Real-Time Energy Optimization: A Simulated Case Study Of The Podium Office Building, New Cairo, Egypt, Maha Fawzy Aly Anber

Mansoura Engineering Journal

The growing demand for smarter and more energy-efficient buildings has led to increasing interest in digital twin (DT) technology for building operation and management. This paper presents a DT framework developed to improve the energy performance of the Podium Office Building in Cairo Festival City, New Cairo, Egypt. A detailed EnergyPlus model, supported by Python-based tools (eppy and pyEnergyPlus), was used to test three HVAC control strategies: a baseline fixed schedule, a real-time DT-informed strategy, and a predictive optimization approach. By integrating local climate data and realistic occupancy patterns, the study assesses energy savings, CO₂ reductions, and indoor comfort improvements. …

3d-Dnn Ion-Eg Model Applications For Ionospheric Characterization Over Egypt: Mans Cors Case Study Of Vtec Variability And Nmf2/Hmf2 Mapping (2020-2024), Ismail Zaher, Zaki Zeidan, Mostafa Rabah, Mahmoud El-Mewafi

Mansoura Engineering Journal

This study introduces an operational evaluation of a deep learning–driven ionospheric modeling system tailored for Egypt, designed to overcome the limitations of conventional empirical approaches in data-sparse regions. The 3D-DNN Ion-EG model was trained on 737,110 COSMIC-2 radio occultation profiles (2020–2024), integrating spatial temporal coordinates with geophysical drivers to generate high-resolution threedimensional electron density distributions. Validation against the MANS CORS station (Mansoura University) demonstrated strong predictive skill (R2 = 0.9337; r = 0.970) under independent testing. Performance analysis across diverse geophysical regimes confirmed the model’s advantage in capturing storm-time and solar-driven disturbances, surpassing empirical models that perform best only under …

Pressure Field Estimation From 2d-Piv Measurements: A Case Study Of Fish Suction-Feeding, Jensine C. Coggin, Duvall Dickerson-Evans, Erin E. Hackett, Roi Gurka

Physics and Engineering Science

Particle image velocimetry (PIV) flow measurements are common practice in laboratory settings in a wide variety of fields involving fluid dynamics, including biology, physics, engineering, and medicine. Dynamic fluid pressure is a notoriously difficult property to measure non-intrusively, yet its variation is a driving flow force and critical to model correctly. Techniques have been developed to estimate the pressure from velocity and velocity gradient measurements. Here, we highlight a novel application of boundary conditions when applying such pressure estimation techniques based on two-dimensional PIV data; the novel method is especially relevant to problems with complex boundary conditions. As such, it …

Folding Architecture “Origami Art-Inspired” Applicability To Sustainable Architecture- Biomuseo As A Case Study, Vitta A. Ibrahim

Mansoura Engineering Journal

The growing need for sustainable architectural solutions in the contemporary era underscores the necessity for interactive architectural applications that can adapt to changing requirements. In architecture, folding systems refer to three-dimensional, foldable structural forms that create unique spatial configurations and possess a wide range of capabilities. Drawing inspiration from origami techniques, this study emphasizes the role of folding systems in generating innovative spatial designs. The research problem arises from the fact that the built environment is a significant contributor to greenhouse gas emissions and energy consumption, necessitating the implementation of smart solutions. The goal of this study is to identify …

Enhanced Generative Convolutional Networks: A Hybrid Algorithm For Refinement Video Classification, Dalal Thair Mahjoub, Hala Bahjat Abdulwahab, Kesra Nermend

Journal of Soft Computing and Computer Applications

Video classification is a vital area of research due to the growing volume of video content in various applications. Accurate category across various resolutions poses challenges, which include adapting to scaling, resizing, and compression. Therefore, this paper introduces an innovative Generative Convolutional Network (GCN) set of rules tailored for multi-resolution video classes. The proposed GCN model utilizes Convolutional Neural Networks (CNNs) combined with generative modeling to enhance the extraction of functions across varying video resolutions, which is crucial for maintaining class robustness in the face of common video adjustments, such as scaling, resizing, and compression. In contrast, traditional fashions frequently …

Latent Action Trajectory Optimization, Rahul Milind Kandekar

Master's Theses

Learning from demonstrations offers a path to bypass the sample inefficiency of reinforcement learning, but obtaining action-labeled expert demonstrations remains expensive and often impractical. Learning from Observations (LFO) addresses this by learning policies from observation-only demonstrations. Recent LFO work relies heavily on behavior cloning: VPT and LAPO use observation-only data combined with limited action labels to train BC policies, while AIME offers an alternative policy inference approach but requires the majority of its training data to have action labels. Through systematic experiments in the Lunar Lander environment, we investigate whether latent action methods can function when state and action dimensionalities …

Mixed Linear Equation–Inequality Systems Over The Pura Vida Neutrosophic Algebra, Muhammad Rayyanu Abdullahi, Abdulhadi Aminu

Neutrosophic Systems with Applications

This paper proposes a neutrosophic extension of max-plus algebra for solving mixed systems of linear equations and inequalities.Classical max-plus algebra is a powerful tool for modeling synchronization in discrete-event systems LastNatpreClose LastNatClose, but it assumes fully deterministic data.To incorporate uncertainty and indeterminacy, we reformulate the framework so that coefficients and variables are expressed as neutrosophic numbers

γ+λI,γ,λ∈ℝ,I∈[0,1],

where I quantifies the degree of indeterminacy.

We redefine the max-plus semiring in this neutrosophic setting, extend solvability and uniqueness results, and adapt the ONEMLP-EI algorithm LastNatpreClose LastNatClose to handle neutrosophic …

Mapping Sustainability To Cybernetic-Generative Artificial Intelligence-Based Education: An Innovative Neutrosophic Orbifold-Lattice Methodology, Mona Mohamed, Ahmed A. Metwaly

Neutrosophic Systems with Applications

The lightning-fast development of artificial intelligence (AI), notably generative artificial intelligence (Gen AI) technologies, has intrigued multiple disciplines, particularly education. In this context, Large Language Models (LLMs) serve as beneficial cognitive resources that address knowledge deficits and provide tailored educational support for learners and staff. For learners, LLMs are regarded as knowledgeable educators who offer prompt, focused responses and rationales to tricky queries. Whereby LLMs for staff, Strength enhancer, automating tedious tasks, and creating intelligent resources.Gen AI’s rapid growth offers enormous obstacles for educational systems, compelling them to discover solutions for these obstacles.

Conceptually, cybernetics is leveraged for bridging the …

Neutrosophic Σ - Baire Spaces, R. Vijayalakshmi, F. Josephine Daisy, M. Simaringa

Neutrosophic Systems with Applications

A Neutrosophic Baire Space extends the concept of Baire Space from classical topology to the realm of neutrosophic topology which deals with sets and spaces where truth, falsehood and indeterminancy are explicitly considered. In this paper the concept of neutrosophic σ - baire spaces are introduced in Neutrosophic topological spaces. Also Neutrosophic σ - dense, Neutrosophic σ - nowhere dense, Neutrosophic σ -first category and Neutrosophic σ - second category sets are defined. Several characterizations of neutrosophic σ - baire spaces are investigated and explained using examples and the conditions under which a neutrosophic topological space becomes a neutrosophic σ …

A Modular Design And Construction Framework For Enhancing The Sustainability Of National Housing Projects In Egypt, Ayman Ahmed Ezzat, Farah Ibrahim El Sahzly

Mansoura Engineering Journal

Egypt’s national housing sector faces mounting sustainability challenges due to outdated design and construction practices that cause material waste, high costs, and inefficient resource use. This study develops a framework for integrating modular design and construction principles into Egypt’s National Housing Projects (NHPs) to strengthen their social, economic, and environmental sustainability. A mixed-method approach combined a literature review, case studies, and a survey of Egyptian Architectural Design Firms (ADFs). The literature review revealed a global consensus on the benefits of modular design and construction, such as improved efficiency, reduced waste, and faster project delivery, yet found limited adoption in Egypt …

Validation Of Innovative Method Of Murine Vertebral Compression Testing, Sarah Staller

The Journal of Purdue Undergraduate Research

Murine vertebral compression testing is a common technique to quantify trabecular bone biomechanics. Having a precise method of vertebral compression is important for aiding researchers in making clinically relevant discoveries in musculoskeletal research. While many methods exist in literature, there has yet to be established a universal protocol for this procedure. Many challenges exist in vertebral compression, such as the irregular shape of the vertebral body (trabecular region of interest), uneven endplate surface morphology, and surrounding cortical processes. Therefore, the aim of this study was to develop a new method of vertebral compression that accounts for these factors and to …

The Automation Of Lamp Biomolecular Assays Using The Eppendorf Epmotion™ 5075 Robotic Pipettor, Shamalaa Sathiasealan

The Journal of Purdue Undergraduate Research

Loop-mediated isothermal amplification (LAMP) is a nucleic acid amplification technique known for its specificity and efficiency in less controlled environments than laboratories. Designing novel LAMP reagents requires strict contamination control, and unlike the more commonly automated polymerase chain reaction, LAMP’s heightened sensitivity poses unique challenges to automation. To address this, we optimized automation procedures for LAMP using a robotic pipettor without altering the core assay itself. This project focuses on minimizing contamination using sealed plates, reducing operator intervention by automating pipetting, and preventing enzyme degradation using cooling plates. Our approach employs pre-slit pierceable seals and cooling blocks to prevent cross-contamination …

Probing The Mechanisms Of Reinforcement Learning: Reinforcement Learning, Ventral Striatal Astrocytes, And The Dynamic Coordination Of Information Seeking With Learning, Fatih Sogukpinar

McKelvey School of Engineering Graduate Student Theses & Dissertations

While reinforcement learning has been a vital component in artificial intelligence and machine learning, there exist many open questions about its implementations and how to improve them, in both minds and machines. Among these are i) the contribution of non-neuronal cell types to reinforcement learning, and ii) information-seeking behavior during reinforcement learning. In this thesis, we studied these main topics pertaining to reinforcement learning. In the first chapter, we examined the role of astrocytes in reinforcement learning, and in the second, we investigated human information seeking during reinforcement learning. Neurons in the human and animal brain have been known to …

Integration Of Algae In Buildings: Challenges And Opportunities, Marwa Said Saad, Mostafa Refaat, Ashraf Nessim

Mansoura Engineering Journal

Buildings produce 40% of energy-associated CO2 emissions and 35% of worldwide energy use which makes it one of the main factors of global warming. The use of bioactive materials on building façades is a creative way to address the aforementioned problems. The biotechnical potential of microalgae architecture to achieve net-zero energy architecture while simultaneously advancing ecological sustainability and occupant well-being has drawn attention. This paper aims to analyzing and investigating techniques of integration of algae in architecture showing the challenges and opportunities of this implementation. Analytical and Comparative analytical method were used in this paper, Initially, a thorough literature review …

Comparative Analysis Of Machine Learning And Statistical Models For Railroad–Highway Grade Crossing Safety, Erickson Senkondo, Deo Chimba, Masanja Madalo, Afia Yeboah, Shala Blue

Civil and Architectural Engineering Faculty Research

Railroad-highway grade crossings (RHGCs) are critical points of conflict between roadway and rail systems, contributing to over 2000 crashes and 250 fatalities annually in the United States. This study applied machine learning methods (ML) techniques to model and predict crash frequency at RHGCs, using a comprehensive dataset from the Federal Railroad Administration (FRA) and Tennessee Department of Transportation (TDOT). The dataset included 807 validated crossings, incorporating roadway geometry, traffic volumes, rail characteristics, and control features. Five ML models—Random Forest, XGBoost, PSO-Elastic Net, Transformer-CNN, and Autoencoder-MLP—were developed and compared to a traditional Negative Binomial (NB) regression model. Results showed that ML …

Optimization Of Research Pipeline To Characterize The Effects Of Atp-Sensitive Potassium Channels Mutations On Native Skeletal Muscle Fibers And Evaluate Potential Drug Therapy, Yuezhou Chen

McKelvey School of Engineering Graduate Student Theses & Dissertations

The ATP-sensitive potassium (KATP) channel is a critical metabolic sensor in skeletal muscle, yet its definitive molecular composition and functional roles remain contested. In this study, I conclusively demonstrate that the Kir6.2/SUR2 complex forms sarcolemmal KATP channel in mouse fast-twitch muscle. Genetic knock-out (KO) of Kir6.2 (Kcnj11−/−) or SUR2 (Abcc9−/−) resulted in a similar phenotype with increased fatigue resistance and a pathological rise in unstimulated resting tension at high-frequency stimulation. In contrast, SUR1 (Abcc8−/−) KO was ineffective. Furthermore, a CRISPR/Cas9 knock-in mouse model of a human SUR2A truncation variant (KCGV/KCGV) recapitulated the abnormal force accumulation, demonstrating that even loss-of-function of …

Utah Lake From Space: Analysis Of Sentinel 2 And Modis Data Shows Spatiotemporal Trends And Patterns In Chlorophyll-A, Turbidity, And Temperature, Kaylee Brook Tanner

Theses and Dissertations

Harmful algal blooms (HABs) are a serious and growing risk to waterbodies around the world. Excessive algal growth, especially when it involves cyanobacteria, impairs the functioning of aquatic ecosystems and threatens the health of humans and animals using the water. There is currently great interest in developing effective prevention and mitigation strategies for these blooms, particularly in ecologically and economically vital freshwater lakes. Such development, however, requires detailed understanding of HAB drivers and dynamics, which can be highly complex and difficult to characterize. High-frequency, high-resolution imagery from earth observation satellites provides spatially and temporally comprehensive data on global lakes--data which …

Methods For The Discovery Of Antibodies Toward Junin Virus Utilizing Yeast Surface Display, Jonathon E. Corral

Doctoral Dissertations and Projects

The importance of this study is to perform antibody discovery as a means to derive novel preventative and therapeutic antibody countermeasures against the Junín virus, to alleviate the potential risk of a global pandemic. The purpose of this methodological study was to develop a protocol that utilizes yeast surface display to discover antibodies, from naïve human antibody libraries, that can bind the Junín Virus antigen. The methodology of yeast surface display employs the galactose-inducible GAL1 promoter to synthesize and express antibody proteins bound to the Aga2p and Aga1p and anchored to the cell wall by glycosyl phosphatidylinositol motif (GPI). The …

Development Of An Iot-Based Energy Theft Detection System For A Single-Phase Smart Meter, Ojo Julius Oladele, Funso Kehinde Ariyo, Samson Oladayo Ayanlade, Ayooluwa Peter Adeagbo, Ismail Adeniyi Adeleke

Al-Bahir

Electricity theft causes annual global losses exceeding $96 billion, severely impacting distribution networks. This paper presents a novel IoT-based system integrating current differential sensing, physical tamper detection, and edge-cloud analytics to detect energy theft in single-phase smart meters. The design employs three ACS712 current sensors to monitor Kirchhoff-compliant current flow at the grid pole, meter input, and load output, coupled with a PIR sensor for cabinet intrusion. A SIM800L GSM module enables real-time theft alerts and remote disconnection, while closed-loop control autonomously restores power after tamper resolution — a feature absent in prior GSM-only systems. An Android application provides geotagged …

Morphological Test Of Areca Nut Fiber Ceramic Membrane Using Scanning Electron Microscopy Energy Dispersive X-Ray Mapping Spectroscopy, Amelia Marzain, Siti Umi Kalsum, Marhadi Marhadi, Ahmad Nabil Shahab

Journal of Materials Exploration and Findings

This study investigates the potential of ceramic membranes derived from areca nut fiber as a cost-effective and environmentally sustainable material for the removal of iron (Fe) and manganese (Mn) from groundwater. Two types of membranes were fabricated: one without activation and one chemically activated using 10% sodium hydroxide (NaOH). The morphological and elemental characteristics of both membranes were analyzed using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) mapping. The concentrations of Fe and Mn before and after treatment were measured using Atomic Absorption Spectroscopy (AAS). The NaOH-activated membrane exhibited a more porous surface structure and higher oxygen content, …

Characterizing Temperature-Dependent Properties Of Fat For Improving High Intensity Focused Ultrasound Simulations, Brian Easthope

Theses and Dissertations

High-intensity focused ultrasound (HIFU) is a non-invasive therapeutic technique that relies on the precise delivery of acoustic energy to ablate diseased tissue. The presence of subcutaneous fat can significantly alter focal accuracy and treatment efficiency due to its distinct thermal and acoustic behavior. This study characterized the temperature-dependent thermal conductivity, thermal diffusivity, specific heat capacity, acoustic attenuation, and acoustic velocity of human subcutaneous fat to improve pretreatment modeling for HIFU therapies. Measurements were performed using a dual needle probe for thermal conductivity and diffusivity, differential scanning calorimetry for specific heat capacity, radiation force balance for attenuation, and through-transmission methods for …

2d-Nanosilicate Carriers For Sustained Delivery Of Vaccine Components, Chih Yun Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Laponite® 2D Nanosilicates (NS) are disc-shaped platelets (~30 nm diameter, ~1 nm thick) with positively charged edges and negatively charged faces, capable of loading proteins, drugs, and nucleic acids via electrostatic interactions to form a house-of-cards gel that sequesters cargo. Here, we evaluated NS for sustained delivery of antigens and Toll-like receptor (TLR) agonists to extend germinal center duration and enhance antibody quality. The model antigen ovalbumin (OVA) was adsorbed onto NS at acidic pH in a ~1:1 ratio, with partial unfolding that remained stable at physiological pH. NS-OVA complexes were efficiently internalized by dendritic cells, with uptake driven primarily …

Modeling The Mojave: A Multiphase, Mixed Methods Phenomenological Investigation Of Novice Understanding Of A Complex Ecological System, Nicole Juliana Thomas

UNLV Theses, Dissertations, Professional Papers, and Capstones

This research explores early college science majors’ conceptions of the Mojave Desert ecosystem as a complex system. A multi-level, explanatory sequential mixed methods design was employed to study college science majors’ understanding of the Mojave Desert ecosystem to better inform science pedagogy. The first level, the quantitative phase of the study, consisted of developing a mathematical representation of twelve ecosystem variables present within the Mojave Desert. The second level, the qualitative phase of the study, consisted of phenomenological semi-structured interviews with 23 early college science majors. The findings of this research suggest that the Mojave Desert operates as a complex, …

Stability Analysis Of Thermohaline Convection With A Time-Varying Shear Flow Using The Lyapunov Method, Kalin Kochnev

Honors Scholar Theses

This work applies the Lyapunov method to identify instabilities and compute the growth rate of a linear time-varying system. The linear system studied describes cold fresh water on top of hot salty water with a periodically time-varying background shear flow. A time-dependent weighting matrix is employed to construct a Lyapunov function candidate. The resulting linear matrix inequalities are discretized in time using the forward Euler method. As the number of temporal discretization points increases, the growth rate predicted by the Lyapunov method or Floquet theory, used for comparison, will converge to the same value obtained from numerical simulations. Furthermore, the …

Application Of Adversarial Volumetric Cnns To 3d Face Generation Using Latent Space Gaussian Embeddings, Ali Raad Abdulkareem, Marwa Jabberi, Islem Jarraya, Tarek M. Hamdani, Khmaies Ouahada, Adel M. Alimi

Iraqi Journal for Computer Science and Mathematics

Although 3D face generation is extensively studied in computer vision, most existing methods prioritize reconstructing 3D geometry from available 2D or 3D inputs rather than generating novel faces directly from latent representations. To bridge this gap, we present the application of Adversarial Volumetric Convolutional Neural Networks (AVCNN), a tailored adaptation of the vanilla 3D Generative Adversarial Network (3D-GAN), to 3D face generation using latent space Gaussian embeddings. We first assemble a custom 3D facial dataset to provide the requisite facial characteristics and to ensure sufficient coverage of geometric variation across identities. The generator, implemented as a decoder, maps latent space …