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Articles 2731 - 2760 of 34156
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Convolutional Neural Networks For Dementia Severity Classification: Ordinal Versus Regular Methods, Ambresh Bhadrashetty, P. Sandhya
Convolutional Neural Networks For Dementia Severity Classification: Ordinal Versus Regular Methods, Ambresh Bhadrashetty, P. Sandhya
Iraqi Journal for Computer Science and Mathematics
Dementia, a chronic neurodegenerative disorder, progressively impairs cognitive functions such as memory, reasoning, learning, and recall, placing a significant burden on patients and healthcare systems. Early and accurate classification of dementia severity is crucial for personalized care and intervention. This study introduces a novel Convolutional Neural Network (CNN) designed to classify dementia into four ordinal severity levels (None, Very Mild, Mild, and Moderate) based on MRI brain scans. Utilizing the extensive Open Access Series of Imaging Studies (OASIS) dataset, which includes 86,437 MRI scans (67,222 ‘none,’ 13,725 ‘very mild,’ 5,002 ‘mild,’ and 488 ‘moderate’), our model addresses severe class imbalance …
Explainable Machine Learning Approach Enables Computer-Aided Identification System For Children Autism Spectrum Disorder (C-Asd), Karrar Hameed Abdulkareem, Zainab Hussein Arif, Mazin Abed Mohammed
Explainable Machine Learning Approach Enables Computer-Aided Identification System For Children Autism Spectrum Disorder (C-Asd), Karrar Hameed Abdulkareem, Zainab Hussein Arif, Mazin Abed Mohammed
Iraqi Journal for Computer Science and Mathematics
Neurodevelopmental disorders like autism spectrum disorder (ASD) cause significant cognitive, linguistic, object identification, communication, and social skills deficits. Although there is currently no cure for autism spectrum disorder (ASD), early detection can aid in diagnosis and implementing effective preventative measures. Artificial intelligence (AI) tools allow for an earlier diagnosis of ASD than was previously possible. Furthermore, many clinical and not clinical attributes can be used for identification of ASD but select the most proper ones still challenge. Therefore, in this study we propose a Computer-Aided Identification System based on machine learning concept and feature selection methods to diagnosis Children Autism …
A Comprehensive Analysis Of Partition Dimensions In Efavirenz Abacavir Lamivudine Doravirine Of Anti-Hiv Drug Structures, R. Nithya Raj, R. Sundara Rajan, Hijaz Ahmad
A Comprehensive Analysis Of Partition Dimensions In Efavirenz Abacavir Lamivudine Doravirine Of Anti-Hiv Drug Structures, R. Nithya Raj, R. Sundara Rajan, Hijaz Ahmad
Iraqi Journal for Computer Science and Mathematics
The partition dimension of a graph in chemical graph theory refers to a graph invariant used to analyze the structural properties of molecules. It represents the minimum number of clusters or resolving partition set required to uniquely identify each vertex in the graph based on the neighborhoods within their respective clusters. In the context of chemical graph theory, the vertices of the graph correspond to atoms, and edges represent bonds between these atoms in a molecular structure. Determining the partition dimension of a chemical graph helps in understanding the relationships between molecular components and their spatial arrangements. It assists in …
Lgformer: Informer-Based Personalized Modeling For Blood Glucose Prediction, Xue Yuewei, Shaopeng Guan, Jia Wanhai
Lgformer: Informer-Based Personalized Modeling For Blood Glucose Prediction, Xue Yuewei, Shaopeng Guan, Jia Wanhai
Turkish Journal of Electrical Engineering and Computer Sciences
Effective diabetes management relies on precise prediction of blood glucose levels to minimize complications. However, the patterns and fluctuations in blood glucose vary significantly among patients, posing a challenge for existing prediction methods. Many current approaches fail to accommodate these individual differences, leading to less reliable predictions. In response to this challenge, we present LGformer, a novel prediction model based on the Informer architecture, designed to enhance both flexibility and accuracy. LGformer improves upon Informer by integrating LSTM and GRU layers into its probSparse Self-attention mechanism, allowing for personalized processing of blood glucose data tailored to each patient's unique profile. …
A New Dxccdita Based Meminductor Emulator And Its Application In Chaotic Oscillator, Bhawna Aggarwal, Shireesh Kumar Rai, Harsh Jain
A New Dxccdita Based Meminductor Emulator And Its Application In Chaotic Oscillator, Bhawna Aggarwal, Shireesh Kumar Rai, Harsh Jain
Turkish Journal of Electrical Engineering and Computer Sciences
This work introduces a new dual-X current conveyor differential input transconductance amplifier (DXCCDITA) based meminductor emulator, alongside its application in chaotic oscillator has also been presented. To realize the designed meminductor emulator, one DXCCDITA, two resistors, and two capacitors are employed. Pinched hysteresis loops are achieved across a wide frequency range spanning from 100 Hz to 1.5 MHz, encompassing both decremental and incremental topologies. Additionally, the proposed circuit offers the flexibility to switch between incremental and decremental configurations using a simple switch. Through examination of non-volatility and transient responses, the efficiency of the presented emulator is evidently demonstrated. To further …
Exploring How Personal And Program Characteristics Inform The Experiences Of Engineering Students Abroad, Kirsten A. Davis, David B. Knight
Exploring How Personal And Program Characteristics Inform The Experiences Of Engineering Students Abroad, Kirsten A. Davis, David B. Knight
School of Engineering Education Faculty Publications
Background
As more universities seek to offer international experiences for engineering students, it is important to design such programs to effectively support student learning abroad. Previous research on study abroad has focused on a limited number of outcomes and therefore failed to consider the diversity of experiences students may have in the same program and the range of learning outcomes they may develop while abroad.
Purpose
We explored student experiences across multiple types of engineering study abroad programs to address the research question: How do the types of significant experiences students highlighted from their time abroad differ based on student …
Characterizing West Florida Shelf Reef Fish Communities Using A Scientific Echosounder, Edmund A. Hughes
Characterizing West Florida Shelf Reef Fish Communities Using A Scientific Echosounder, Edmund A. Hughes
USF Tampa Graduate Theses and Dissertations
The advancement and application of non-invasive fisheries survey technologies, such as the scientific echosounder, have significantly enhanced our understanding of fish populations and their habitats, more recently in regions where traditional sampling methods are limited, such as complex reef habitats. This research, conducted as part of the Continental Shelf Characterization, Assessment, and Mapping Project (C-SCAMP) on the West Florida Shelf, leverages acoustic and visual technologies to investigate the distribution of fish densities, fish target strength and length relationships, and the relationship between seafloor topography and fish biomass distribution.
The first study compared reef fish densities estimated from near-concurrent acoustic (Simrad …
Sdf-1Α Mediates Primary Tumor Escape In Glioblastoma Through Activation Of Mesenchymal Transitions, Charles T. Froman-Glover
Sdf-1Α Mediates Primary Tumor Escape In Glioblastoma Through Activation Of Mesenchymal Transitions, Charles T. Froman-Glover
The Cardinal Edge
Glioblastoma (GBM), a highly aggressive primary brain tumor originating in glial cells, poses a significant challenge due to its rapid growth and invasive nature within healthy brain tissue.
Current treatments involve surgical resection, chemotherapy, and radiation. These treatments alone are not enough to cure this disease, and a better understanding of the mechanics of the tumor's micro-environment is imperative to furthering the field of cancer research. This research focuses on understanding the tumor microenvironment's impact, specifically investigating the role of stromal cell-derived factor 1 (SDF-1) mechanics on GBM aggressiveness. SDF-1 is known to facilitate disease progression by facilitating chemotaxis toward …
Motivating Sustainability Through The State Of Biologically Inspired Design, Bryan Watson
Motivating Sustainability Through The State Of Biologically Inspired Design, Bryan Watson
Sustainability Conference
There are multiple arguements for sustainability, but one that resonates with environmentalists and the public alike is the need for preservation to all us to discovery natural solutions to our problems. Common examples often given include medical discoveries, unique mechanisms, and new materials. This presentation focuses on two ideas to motivate sustainability. First, what is the current state of biologically inspired design? Is there more to learn from nature? To answer these questions, recent research is presented which examined 660 Biologically Inspired Design samples from three data sources: Google Scholar, Google News, and the Asknature.org “Innovations” database. The data were …
The Impact Of Cumulative And Acute Loading On Achilles Tendon Health, Performance, And Reported Pain In Collegiate Gymnasts, Julio Serrano Samayoa
The Impact Of Cumulative And Acute Loading On Achilles Tendon Health, Performance, And Reported Pain In Collegiate Gymnasts, Julio Serrano Samayoa
Electronic Theses and Dissertations
Gymnasts are at a high risk of Achilles tendon (AT) injuries due to intense loads during takeoffs and landings. To better understand better the relationship between impact loading and its effects on tendon adaptation and athletic performance, this study uses Inertial Measurement Units (IMUs) to track AT loading across a collegiate gymnastics season. This data were compared against physiological and athletic performance metrics, obtained through force plates and ultrasound imaging, to explore how mechanical load influences reported pain and athletic performance. Results varied, with cumulative impacts being correlated with improved jump height (Spearman 0.362, Pearson 0.348), while peak power and …
Beyond The Waterfall: A Review Of Project Management Methodologies In Stem, Yessenia Henriquez
Beyond The Waterfall: A Review Of Project Management Methodologies In Stem, Yessenia Henriquez
Undergraduate Research Symposium Posters
Project management has been exercised from history's early stages to concurrent practices today. It has evolved from the early stages of the Gantt chart and five primary principles to well-renowned project management methodologies such as Waterfall and Agile. This literature review focuses on comprehending four project management methodologies (Waterfall, Agile, Kanban, and Scrum), learning their criteria and frameworks, and their application in a specific STEM environment when applicable. This work reviews the recent research literature about these four methods. An overview of project management certificates and guidelines is covered as well. Waterfall is known to be a traditional method, having …
Characterizing The Mechanical And Visoelastic Properties Of Sodium Alginate, Vesper Evereux
Characterizing The Mechanical And Visoelastic Properties Of Sodium Alginate, Vesper Evereux
Undergraduate Research Symposium Posters
A crucial part of tissue engineering lies in understanding and characterizing the mechanical and viscoelastic properties of various types of biomaterials. Understanding these properties allows better biomaterials to be produced with characteristics more similar to those of the human body and with better biocompatability. In this study, sodium alginate was chemically crosslinked with calcium chloride and subsequently tested for it's instantaneous Elastic Modulus, instantaneous Shear Modulus, and equivalent viscosity using indentation testing methods consisting of a stress-relaxation test and nonlinear curve-fitting analysis. Two and three millimeter indentation tests were performed using a low-cost and portable device built in-lab that resulted …
Detection Of Methane Leaks By The Use Of Mid-Range Infrared Camera, Jared Rosario, Oscar Salcido
Detection Of Methane Leaks By The Use Of Mid-Range Infrared Camera, Jared Rosario, Oscar Salcido
Undergraduate Research Symposium Posters
Timely detection of methane leaks from natural gas infrastructure, like pipelines and valves, is essential for mitigating environmental and safety risks. This research focuses on using mid-wave infrared (MwIR) cameras on unmanned aerial systems (UAS) to detect leaks. By leveraging machine learning, the study aims to develop an efficient, real-time methane inspection system that operates directly on embedded processors on UAS platforms.
This project employs the FLIR G300a OGI camera for remote gas inspection, utilizing video preprocessing and optical flow to mask gas plumes in footage. The YOLOv8 deep learning model is used to detect gas pixels and segment the …
Hybrid Energy Systems: Synergy Margin And Control Co-Design, Mario Garcia Sanz
Hybrid Energy Systems: Synergy Margin And Control Co-Design, Mario Garcia Sanz
Faculty Scholarship
Extraordinary properties emerge from subsystems' interactions. Hybrid energy systems (HESs) are a promising concept that could change the renewable energy landscape. By co-designing generation, storage, and conversion technologies, HESs can provide new electrical power services, increase grid stability and control authority, and generate energy and/or nonenergy products such as electricity, hydrogen, ammonia, heat, digital data, or fresh water. This article discusses some conditions the co-design of HESs should follow to optimize the combined system (synergy), avoiding deterioration (dysfunction). It introduces some technoeconomic synergy conditions, develops a synergy margin, and analyses several case studies, exploring also the control co-design methodology to …
Phagolysosomes Break Down The Membrane Of A Non-Apoptotic Corpse Independent Of Macroautophagy, Shruti Kolli, Cassidy J. Kline, Kimya M. Rad, Ann M. Wehman
Phagolysosomes Break Down The Membrane Of A Non-Apoptotic Corpse Independent Of Macroautophagy, Shruti Kolli, Cassidy J. Kline, Kimya M. Rad, Ann M. Wehman
Biological Sciences: Faculty Scholarship
Cell corpses must be cleared in an efficient manner to maintain tissue homeostasis and regulate immune responses. Ubiquitin-like Atg8/LC3 family proteins promote the degradation of membranes and internal cargo during both macroautophagy and corpse clearance, raising the question how macroautophagy contributes to corpse clearance. Studying the clearance of non-apoptotic dying polar bodies in Caenorhabditis elegans embryos, we show that the LC3 ortholog LGG-2 is enriched inside the polar body phagolysosome independent of autophagosome formation. We demonstrate that ATG-16.1 and ATG-16.2, which promote membrane association of lipidated Atg8/LC3 proteins, redundantly promote polar body membrane breakdown in phagolysosomes independent of their role …
Smartphone Haptics Can Uncover Differences In Touch Interactions Between Asd And Neurotypicals, Ivonne Monarca, Franceli L. Cibrian, Isabel López Hurtado, Monica Tentori
Smartphone Haptics Can Uncover Differences In Touch Interactions Between Asd And Neurotypicals, Ivonne Monarca, Franceli L. Cibrian, Isabel López Hurtado, Monica Tentori
Engineering Faculty Articles and Research
Utilizing touch interactions from smartphones for gathering data and identifying digital markers for screening and monitoring neurological disorders, such as Autism Spectrum Disorder (ASD), is an emerging area of research. Smartphones provide multiple benefits for this kind of study, including unobtrusive data collection via built-in sensors, integrated haptic feedback systems, and the capability to create specialized applications. Acknowledging the significant yet understudied presence of tactile processing differences in individuals with ASD, we designed and developed Feel and Touch, a mobile game that leverages the haptic capabilities of smartphones. This game provides vibrotactile feedback in response to touch interactions and collects …
Synthesis And Characterization Of Titanium And Vanadium Nitride–Carbon Composites, Helia Magali Morales, David A. Sanchez, Elizabeth M. Fletes, Michael Odlyzko, Victoria Padilla, Mataz Alcoutlabi, Jason Parsons
Synthesis And Characterization Of Titanium And Vanadium Nitride–Carbon Composites, Helia Magali Morales, David A. Sanchez, Elizabeth M. Fletes, Michael Odlyzko, Victoria Padilla, Mataz Alcoutlabi, Jason Parsons
Mechanical Engineering Faculty Publications
Titanium nitride and vanadium nitride–carbon-based composite systems, TiN/C and VN/C, were prepared using a new synthesis method based on the thermal decomposition of titanyl tetraphenyl porphyrin (TiOTPP) and vanadyl tetraphenyl porphyrin (VOTPP), respectively. The structure of the TiN/C and VN/C composite materials, as well as their precursors, were characterized using Fourier Transformed Infrared Spectroscopy, X-Ray diffraction (XRD), X-Ray energy dispersive (EDS) and X-Ray photoelectron spectroscopy (XPS). Morphologies of the TiN/C and VN/C composites were examined by means of scanning electron (SEM) and transmission electron (TEM) microscopy. The synthesis of the non-metalated tetraphenyl porphyrin, the titanium, and vanadium tetraphenyl porphyrin complexes …
Effects Of Surface Treatment On Adhesive Performance Of Composite-To-Composite And Composite-To-Metal Joints, Nikhil Paranjpe, Md. Nizam Uddin, Akm S. Rahman, Ramazan Asmatulu
Effects Of Surface Treatment On Adhesive Performance Of Composite-To-Composite And Composite-To-Metal Joints, Nikhil Paranjpe, Md. Nizam Uddin, Akm S. Rahman, Ramazan Asmatulu
Publications and Research
This study deals with the long-running challenge of joining similar and dissimilar materials using composite-to-composite and composite-to-metal joints. This research was conducted to evaluate the effects of surface morphology andsurfacetreatments onthemechanicalperformanceofadhesively bonded joints used for the aircraft industry. A two-segment, commercially available, toughened epoxy was chosen as the adhesive. Unidirectional carbon fiber prepreg and aluminum 2021-T3 alloys were chosen for the composite and metal panels, respectively. Surface treatment of the metal included corrosion elimination followed by a passive surface coating of Alodine®. A combination of surface treatment methods was used for the composite and metal specimens, including detergent cleaning, plasma …
Can The Effluent From Wastewater Stabilization Ponds Be Effectively Managed For Health And Nutrient Recovery?, Michael Glass
Can The Effluent From Wastewater Stabilization Ponds Be Effectively Managed For Health And Nutrient Recovery?, Michael Glass
USF Tampa Graduate Theses and Dissertations
Wastewater stabilization ponds, such as facultative and maturation lagoons, have been shown to be effective processes to manage conventional water quality parameters found in domestic wastewater. The main goal of this thesis is to explore whether wastewater stabilization ponds can simultaneously reduce pathogens to safe levels while supporting agricultural activities through nutrient recovery. A large dataset for water quality of wastewater lagoon effluent in the U.S. was obtained at the state level and combined into regional southern and northern locations. Analysis of data showed there was significant difference in lagoon effluent concentration between northern and southern states for the water …
Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl
Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl
Faculty Publications
Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.
Sound Innovations For Biofabrication And Tissue Engineering, Mengxi Wu, Zhiteng Ma, Zhenhua Tian, Joseph Rich, Xin He, Jianping Xia, Ye He, Kaichun Yang, Shujie Yang, Kam W. Leong, Luke P. Lee, Tony Jun Huang
Sound Innovations For Biofabrication And Tissue Engineering, Mengxi Wu, Zhiteng Ma, Zhenhua Tian, Joseph Rich, Xin He, Jianping Xia, Ye He, Kaichun Yang, Shujie Yang, Kam W. Leong, Luke P. Lee, Tony Jun Huang
Faculty Publications
Advanced biofabrication techniques can create tissue-like constructs that can be applied for reconstructive surgery or as in vitro three-dimensional (3D) models for disease modeling and drug screening. While various biofabrication techniques have recently been widely reviewed in the literature, acoustics-based technologies still need to be explored. The rapidly increasing number of publications in the past two decades exploring the application of acoustic technologies highlights the tremendous potential of these technologies. In this review, we contend that acoustics-based methods can address many limitations inherent in other biofabrication techniques due to their unique advantages: noncontact manipulation, biocompatibility, deep tissue penetrability, versatility, precision …
Nonequilibrium Plasma Synthesis And Processing Of Iii-Nitride Materials, Dillon Patrick Moher
Nonequilibrium Plasma Synthesis And Processing Of Iii-Nitride Materials, Dillon Patrick Moher
McKelvey School of Engineering Graduate Student Theses & Dissertations
Nitrogen is abundant on Earth as its diatomic form, and human activity has generated a significant demand for nitrogen-containing compounds. However, its triple bond energy of 941 kJ/mol makes it a poor reactive species in the ground state. Nitrogen-containing nonequilibrium plasmas are made up of background gas, electrons, ions, and a multitude of excited states of nitrogen or even atomic nitrogen. Many of these species have rather high reactivity. As such, the plasma medium is of great potential for driving chemical reactions that involve nitrogen as a reactant, i.e., nitrogen fixation into compounds like ammonia, high-energy-density polynitrogen compounds, and metal-nitride …
Nonequilibrium Plasma Synthesis And Processing Of Iii-Nitride Materials, Dillon Patrick Moher
Nonequilibrium Plasma Synthesis And Processing Of Iii-Nitride Materials, Dillon Patrick Moher
McKelvey School of Engineering Graduate Student Theses & Dissertations
Nitrogen is abundant on Earth as its diatomic form, and human activity has generated a significant demand for nitrogen-containing compounds. However, its triple bond energy of 941 kJ/mol makes it a poor reactive species in the ground state. Nitrogen-containing nonequilibrium plasmas are made up of background gas, electrons, ions, and a multitude of excited states of nitrogen or even atomic nitrogen. Many of these species have rather high reactivity. As such, the plasma medium is of great potential for driving chemical reactions that involve nitrogen as a reactant, i.e., nitrogen fixation into compounds like ammonia, high-energy-density polynitrogen compounds, and metal-nitride …
Development Of Machine Learning-Based Tool For Prediction Of Long-Term Field Performance Of Asphalt Concrete Overlays In A Hot And Humid Climate, Elise Mansour
LSU Doctoral Dissertations
The performance of pavement plays a critical role in Maintenance, Rehabilitation and Reconstruction (MR&R) for highway agencies. Reliable and accurate estimation of pavement performance can be instrumental in prioritization of the limited resources and funding for highway agencies. The latter requires robust prediction models that can handle large-scale, real-world data and can forecast pavement performance in the long run. Unfortunately, the traditional performance prediction models have raised concerns regarding their efficiency and accuracy. It is because these models were based on a limited number of explanatory variables, were not up-to-date and were designed for forecasting short-term (up to five years) …
Automated Solutions For Hydroponic Plant Growth, Sydney Mcclure, Adam Lachguar
Automated Solutions For Hydroponic Plant Growth, Sydney Mcclure, Adam Lachguar
Sustainability Conference
Within the past year, Project H.O.M.E. has been focusing on the design and development of a semi-automatic hydroponic system specifically for sustaining plant life in Martian-like conditions. Given the significance of extended space-based travel, where the duration of human life in space is a crucial factor, growing food becomes imperative. This project has integrated electrical engineering and computer science, with features like automated pH testing and sensor-based evaluations. Key functionalities, including timed watering and automatic adjustments, were coded to enhance plant care. Initially, the project’s comprehensive research and strategic planning resulted in detailed blueprints and computer-aided design models for the …
Techno-Economic Analysis Of Waste Plastic Gasification, Henrik Don-Yor Ketting
Techno-Economic Analysis Of Waste Plastic Gasification, Henrik Don-Yor Ketting
Master's Theses
The increasing generation of plastic waste and its environmental impact has driven interest in alternative disposal methods such as gasification. This study presents a techno-economic analysis of the gasification of waste plastics, specifically polypropylene (PP) and polyethylene (PE), to produce syngas. A two-stage process—thermal decomposition followed by steam reforming—was simulated using Aspen Plus. The simulation results were validated against experimental data available in the literature. The economic analysis was conducted by estimating the capital and operating costs of the gasification plant, considering factors such as feedstock costs, energy requirements, and syngas purification systems. Net Present Value Calculations were used to …
Machine Learning-Driven Process Analysis And Optimization In Solid-State Welding And Fusion-Based Additive Manufacturing, Radif Uddin Ahmed
Machine Learning-Driven Process Analysis And Optimization In Solid-State Welding And Fusion-Based Additive Manufacturing, Radif Uddin Ahmed
Master's Theses
In the modern era of advanced manufacturing, optimizing process parameters is pivotal in ensuring the quality and reliability of sophisticated component fabrication. This study presents a novel, data-driven approach to parameter optimization in two cutting-edge manufacturing techniques: Friction Stir Welding (FSW) and Laser Powder Bed Fusion (LPBF). By leveraging machine learning methodologies, this research addresses the critical challenge of efficiently determining optimal process parameters, a task traditionally relying on time-consuming and resource-intensive trial-and-error methods. This study will lead to a robust data-driven framework for process analysis of more advanced manufacturing techniques like the Additive Friction Stir Deposition (AFSD) process. Friction …
Identifying Hidden Factors Influencing Soil Olsen-P In An Alkaline Calcareous Soil Using Machine Learning And Geostatistical Techniques, Moussa Bouray, Mohammed Bayad, Adnane Beniaich, Ahmed G. El-Naggar, Rebecca Muenich, Kahlil El Mejahed, Abdallah Oukarroum, Mohamed El Gharous
Identifying Hidden Factors Influencing Soil Olsen-P In An Alkaline Calcareous Soil Using Machine Learning And Geostatistical Techniques, Moussa Bouray, Mohammed Bayad, Adnane Beniaich, Ahmed G. El-Naggar, Rebecca Muenich, Kahlil El Mejahed, Abdallah Oukarroum, Mohamed El Gharous
Biological and Agricultural Engineering Faculty Publications and Presentations
Phosphorus (P) deficiency is one of the major constraints for sustainable crop production in calcareous soils. This study aimed to elucidate the key soil characteristics modulating the variability of soil Olsen P in these typical soils. A comprehensive soil sampling initiative (1.5 samples per hectare) was conducted on a 100-ha farm, considering 31 attributes that included soil physical and chemical properties, and geographic attributes. Three machine learning algorithms—partial least squares regression (PLSR), random forest (RF), and cubist regression (CR)—were employed to understand key variables controlling soil Olsen P. Furthermore, the same data set was used to spatially map the …
Antimicrobial Activity And Photostability Of Cationic Conjugated Polyelectrolytes, Mohammed Ismael Khalil
Antimicrobial Activity And Photostability Of Cationic Conjugated Polyelectrolytes, Mohammed Ismael Khalil
Chemical and Biological Engineering ETDs
Antimicrobial resistance is a growing global health concern, driving the need for novel
therapeutic strategies. This study explores the antimicrobial efficacy of conjugated
polyelectrolytes (CPEs) and oligo-phenylene ethynylenes (OPEs) in bacterial and viral
inactivation. Quantitative analysis revealed that light-activated CPEs and OPEs
effectively reduced bacterial viability within minutes, with significant log reductions
observed under both light and dark conditions. Additionally, the antiviral potential of a
cationic conjugated oligomer was investigated, demonstrating rapid and near-complete
inactivation of SARS-CoV-2 under visible light, both in solution and on filter materials.
Further analysis of their photophysical properties revealed that, even after
photobleaching, the compounds …
Investigating Spatiotemporal Trends Using Precursory Signatures: Implications To Develop Short-Term Earthquake Forecasting Techniques In Sumatra-Andaman Region, Ramya Jeyaraman J
Investigating Spatiotemporal Trends Using Precursory Signatures: Implications To Develop Short-Term Earthquake Forecasting Techniques In Sumatra-Andaman Region, Ramya Jeyaraman J
Theses and Dissertations
Earthquake forecasting is a challenging field due to Earth's heterogeneous nature. This research aims to develop a short-term earthquake forecasting model by analyzing spatiotemporal trends and precursory signatures in the Sumatra-Andaman region, known for its high seismic activity and tsunami risk. The study adopts an interdisciplinary approach, integrating solid earth tides (SET), micro shocks, and outgoing longwave radiation (OLR) to gain deeper insights into seismic nucleation processes. The research begins by using Singular Spectral Analysis (SSA) to identify potential seismically vulnerable areas through the analysis of irregularities in SET.
A spatiotemporal analysis of micro shocks is conducted to assess the …