Physical Sciences and Mathematics Commons^™

Inhibition Of Mif With An Allosteric Inhibitor Triggers Cell Cycle Arrest In Acute Myeloid Leukemia, Georgios Pantouris, Leepakshi Khurana, Pathricia Tilstam, Alison Benner, Thomas Yoonsang Cho, Martin Lelaidier, Mathieu Perrée, Zoe Rosenbaum, Lin Leng, Francine Foss, Vineet Bhandari, Amit Verma, Richard Bucala, Elias J. Lolis

Pacific Faculty Work

Macrophage migration inhibitory factor (MIF) is a key modulator of innate and adaptive immunity that has been extensively reported to promote tumor cell survival, proliferation, and metastasis. A recent study focusing on the microenvironment of acute myeloid leukemia (AML) showed that pharmacological inhibition of MIF signaling, in vitro as well as in vivo, reduces AML cell survival. Such data highlights the crucial role of MIF in AML pathogenesis and support the efforts for developing selective MIF modulators. Here, we report the identification and crystallographic characterization of a MIF inhibitor (compound 1) with an allosteric binding motif. Single point screening of …

Improving Efficiency Of Wind Flow Modeling For Wildfire Applications Using Analytical Parameterization And Neural Networks, Laura Jane Housley

Theses and Dissertations

We model wind velocity fields for applications in wildfire modeling. We improve the accuracy of the mass-conserving WindNinja solver without compromising efficient temporal complexity. We consider two approaches: the parameterization method and the neural network method. In the parameterization method, we analyze eddies in the wake of obstacles by parameterizing cavity zones as inspired by the research by Kaplan & Dinar in 1996. Kaplan & Dinar parameterize cavity zones around rectangular buildings, and we approximate a continuous landscape with rectangular buildings in order to extend this parameterization to complex terrains. In the neural network method, we train a U-net CNN …

Re: Bpsou Superfund Stormwater Operation And Maintenance (O&M) Request For Maintenance – Kelley Stormwater Channels, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Combinatorial Rigidity And Flexibility Of Simplicial 2-Complexes With Few Vertices, Serge A. Lawrence, Abdulkarim M. Magomedov, Olga I. Chelyapina, Valentina M. Rudenko

Theory & Applications of Graphs

We study the problem of reconstruction of a simplicial 2-complex from its 1- skeleton together with the prescribed quantities of 2-simplices at each 1-simplex, under the restriction that these quantities are bounded above by 2. It is a known fact that a 2-complex is uniquely reconstructible, or “combinatorially rigid”, if it has 5 or fewer vertices. In this paper “combinatorially flexible” 2-complexes (that is, non-uniquely reconstructible from their 1-skeletons) with 6 vertices are characterized in terms of necessary 2-subcomplexes.

Global Ocean Bottom Temperature Observation Design: Observing System Simulation Experiments For Strategic Deployment Of Smart Subsea Cables, Karen E. Renninger-Rojas

LSU Master's Theses

Deep-ocean observations below 2000 meters remain limited, restricting our ability to model global ocean processes critical to climate prediction. This thesis evaluates the potential of SMART (Science Monitoring and Reliable Telecommunications) subsea cables to address these observational gaps by conducting Observing System Simulation Experiments (OSSEs) and adjoint sensitivity analyses using the MITgcm ocean model and ECCO outputs.

Vertical decorrelation analysis showed that temperature and salinity in key regions decouple from the upper ocean beyond 2000 m. Over 60% of the proposed SMART cable sites exhibited decorrelation depths exceeding Argo’s maximum sampling depth, highlighting their strategic value for deployment.

A comparison …

Advancing Aerial Survey Techniques For Non-Breeding Waterfowl Populations: A Comprehensive Review And Application In Northeastern Louisiana, Victoria L. Drake

LSU Master's Theses

Aerial surveys play a crucial role in monitoring North America's waterfowl populations and habitat conditions, and consistency across geographies and years allows biologists to track trends through time. The goal of this project was to redesign the northeastern portion of the Louisiana wintering waterfowl survey to align with statistically robust transect surveys conducted in neighboring states within the Mississippi Alluvial Valley. To identify the optimal sampling method, we evaluated three transect weighting schemes: stratified random (unweighted), stratified by watershed, and stratified by expert opinion. Approximately 10% of the total sampling area was randomly selected for each survey period, adhering to …

Inquiry-Style Planetarium Activities, Emma Rasmussen Groberg

Theses and Dissertations

Introductory astronomy students often face challenges in exploring their own ideas and investigating astronomical phenomena due to the limitations of nighttime observation and weather conditions. Planetariums overcome these barriers by simulating the night sky, making it accessible during class sessions regardless of external conditions. This provides an opportunity to engage students in inquiry-based activities, where they are presented with a scenario and encouraged to use their own reasoning to reach conclusions. In this study, we implemented inquiry-based activities in PHSCS 127 using the planetarium as an investigative tool. We developed four activities designed to help students explore their ideas and …

Modeling The Kepler Systems With Multiple Transiting Planets, Daniel Kempton Jones

Theses and Dissertations

As the study of exoplanets, planets not in our solar system, has developed, new observational constraints have illuminated the formation and evolution of planetary systems. Among these observations, the true distributions of planetary mass, radius, and density are at the forefront. NASA's Kepler Space Telescope has provided an enormous wealth of data on the exoplanet radius distribution as well as a significant fraction of mass measurements through the detection of planet-planet dynamical interactions. The best method for studying these exoplanetary systems is with a photodynamical model which combines an n-body integrator with lightcurve model to generate synthetic lightcurves. To support …

Securing Edge-Iiot Networks: A Comprehensive Ensemble-Based Ddos Detection System, Fariba Laiq, Feras Al-Obeidat, Adnan Amin, Fernando Moreira

All Works

As the number of Internet of Things (IoT) devices increases daily due to the rapid growth in technology, every device and network is vulnerable to attacks because it is exposed to the internet. Denial of Service (DoS) is a prevalent type of intrusion on the IoT network in which the server becomes down due to flooding requests. Distributed Denial of Service (DDoS) is a special type of DoS attack where the network of malicious computers called botnet consumes the target's system resources by flooding the requests. Edge computing is closely related to Industrial Internet of Things (IIoT), and industry 4.0. …

Understanding Flow: An Experimental Analysis Of A Magnetohydrodynamic Fluid Pump, Quintin Yates, Emily Hawkins

Honors Thesis

When a magnetic field and electrical current are perpendicular to each other, an ionized fluid will experience a force called the Lorentz force. This force can be applied to create a pump. These pumps have potential applications in desalination and fluid systems in space. The technology is new, and still not well understood but are a potential alternative to typical mechanical pumps. This thesis develops a comprehensive experimental understanding of the fluid flow through a 3D-printed magnetohydrodynamic (MHD) pump. Lagrangian particle tracking (LPT) uses neutrally buoyant particles and a camera system to collect quantitative velocity information of a system. Particle …

Ai Meets Economics: Can Deep Learning Surpass Machine Learning And Traditional Statistical Models In Inflation Time Series Forecasting?, Ezekiel N.N. Nortey, Edmund F. Agyemang, Enoch Sakyi-Yeboah, Obu-Amoah Ampomah, Louis Agyekum

School of Mathematical & Statistical Sciences Faculty Publications

This study examined the forecasting ability of deep learning (DL) and machine learning (ML) models against benchmark traditional statistical models for the monthly inflation rates in the USA. The study compared various DL and ML models like transformers, linear regression, gradient boosting (GB), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost) with traditional baseline time-series models like autoregressive integrated moving averages (ARIMA) and exponential smoothing (ETS) with Holt-Winters seasonal method utilizing data sourced from the Federal Reserve Bank of St. Louis. The study consistently showed that all DL and ML models outperformed the traditional approaches. In particular, the Transformer (RMSE …

Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita

Neutrosophic Systems with Applications

Graph theory explores networks composed of nodes (vertices) and their connections (edges). A graph class is a collection of graphs that share common structural properties, defined by specific rules or constraints. This paper examines various models of uncertain graphs, including Fuzzy, Intuitionistic Fuzzy , Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs. In particular, this study focuses on Bipolar Graphs and Interval-valued Graphs, analyzing them within the frameworks of Fuzzy, Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs.

A Comprehensive Intelligent Traffic Monitoring System Based On A Novel Integration Of Neutrosophic Multi-Criteria Decision-Making Techniques, Mai Mohamed, Amira Salam, Rana Muhammad Zulqarnain, Muhammad Gulistan

Neutrosophic Systems with Applications

With the spread of road accidents and traffic congestion that costs countries and governments a lot of money in addition to the loss of human lives, and since traditional methods of monitoring traffic have not been as effective as desired, attention has been drawn to the search for more effective solutions to the problem of monitoring and regulating traffic. With the spread of technology and the Internet of Things, UAVs have emerged as a promising tool for monitoring traffic, as they can fly for a sufficient period and operate in difficult climatic conditions, in addition to their ability to monitor …

Appraisal Of Uncertainty-Driven Financial Performance: Bringing Multi-Criteria Decision Making Techniques With Neutrosophic Theory, Mona Mohamed, Nurhan Alaa, Eman Sayed

Neutrosophic Systems with Applications

Evaluating financial performance is essential yet challenging due to various factors, including ambiguity, insufficient information, and conflicting evaluation criteria. Conventional Multi-Criteria Decision-Making (MCDM) techniques often struggle to manage these complexities effectively. To address these limitations and enhance financial performance assessments, this research proposes an innovative approach integrating Single-Valued Neutrosophic Sets (SVNS) with established MCDM methodologies. SVNS uniquely manages uncertainty by concurrently quantifying degrees of truth, indeterminacy, and falsity within financial data. This research specifically employs entropy-based weighting methods integrated with Additive Ratio Assessment (ARAS) and Multi-Objective Optimization by Ratio Analysis (MOORA) methodologies in the SVNS environment to systematically rank enterprises …

Leveraging Hypersoft Set To Optimize Livestock In The Era Of Unmanned Aerial Vehicles, Alaa Salem, Mona Mohamed, Nebojsa Bacanin, Mohamed Abouhawwash

Neutrosophic Systems with Applications

Due to urbanization and industrialization, rapid global change and the potential loss of arable land, agricultural output must rise in production levels and harvest, distribute, and use resources more efficiently. It is believed that using technology on livestock would help meet the expanding population's demand for food. Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) integration in conventional farming has transformed operations, providing farmers with greater productivity, improved decision-making, and sustainability. We assume that there are enough UAVs to cover the entire pasture, and our goal is to identify the best UAVs. Accordingly, determining the best type of UAVs …

Nash Equilibrium Solutions For Continuous Static Games Under Neutrosophic Environment, M. G. Brikaa

Neutrosophic Systems with Applications

Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real life problems. This paper presents a novel approach to solving a new class of continuous static games within a neutrosophic framework. In the proposed methodology, the neutrosophic continuous static games are redefined into two separate crisp problems: the lower problem and the upper problem. The study further establishes the necessary conditions for determining equilibrium strategies in neutrosophic continuous static games. To demonstrate its effectiveness and practical applicability, the proposed method is validated through a numerical example.

Speed Of Shear Waves As A Function Of Frequency In Micellar Fluid, Michael Basha

Honors Theses

The purpose of this experiment was to investigate the frequency dependence of shear wave speed in a micellar fluid. A high-concentration CTAB-NaSal micellar fluid seeded with microspheres was used in the experiment. Shear waves were generated using a wave driver and a function generator, while a high-speed camera captured video recordings. Since the frequency of the wave driver producing the shear waves in the micellar fluid is a constant value set by the experimenter, changes in shear wave speed can be determined by measuring their wavelengths at different frequencies.The captured video was then broken down into frames using MATLAB. These …

Assessing The Sustainable Blockchain-Metaverse-Iot Platform In The Healthcare Industry: An Intelligent Decision Support Model, Ibrahim M. Hezam, Ahmed M. Ali, Ibrahim A. Hameed, Karam Sallam, Mohamed Abdel-Basset

Neutrosophic Systems with Applications

Healthcare services must fulfill patients' desires for secure data sharing and high accessibility. Blockchain technology, through blockchain platforms (BPs), can overcome healthcare challenges. This study develops a decision-making methodology for selecting the best BP, by integrating blockchain with IoT and Metaverse, the proposed approach ensures data integrity, quality, privacy and security, secure data sharing, and interoperability. The decision-making methodology uses the multi-criteria decision-making (MCDM) methodology to handle conflicting criteria. Two MCDM methods are used in this study: CRiteria Importance Through Intercriteria Correlation (CRITIC) for weight computation, and Ranking of Alternatives with Weights of Criterion (RAWEC) for alternative ranking. To deal …

A Performance Comparison Between Two Speech-To-Asl-Gesture-Projection Translation Implementations, Alexandra Kashani Motlagh, Shikha Mehta, Ishfaq Ahmad, Addison Clark, Hansheng Lei

Informatics and Engineering Systems Faculty Publications

Millions of people with hearing disabilities use sign language for communication, creating a communication gap with those who are not fluent in ASL (American Sign Language). This paper aims to introduce an ASL interpreter system using a smart-glasses-based augmented reality system. We begin by introducing and comparing two models that translate spoken language into ASL poses. The first system translates spoken text to ASL Gloss, an intermediate representation, before generating ASL poses. The second system directly translates the text to ASL poses. Our analysis shows that using ASL Gloss as an intermediate step significantly improves the translation speed. We then …

Expanding The Horizons Of Nonagonal Neutrosophic Numbers As A Versatile Framework For Decision-Making And Scientific Applications In Covid-19, Muhammad Naveed Jafar, Kainat Muniba, Hamiden Abd El-Wahed Khalifa, Fahd Jarad

Neutrosophic Systems with Applications

In this article, the concept of nonagonal neutrosophic numbers has been introducing in the disjunctive frame of reference. We also proposed the dependency and independency of membership function in regards to nonagonal neutrosophic number. We also introduce a new score function and its computation also formulated in a distinct rational viewpoint. We developed the concept of weighted arithmetic averaging operator and weighted geometric averaging operator for nonagonal neutrosophic numbers. It will open new doors for MCDM and develop the concept with new approaches. Additionally, we analyze the effect of COVID-19 for different ages.

An Approach To Model Uncertainty In Fluid Behaviour With Navier-Stokes Equations In Neutrosophic Environment, Muhammad Saeed, Attia Hameed, Neha Andaleeb Khalid, Muhammad Salman Habib

Neutrosophic Systems with Applications

The complex discipline of fluid dynamics examines the behavior of fluids and their interactions with adjacent objects. The Navier-Stokes equations are very important for explaining how fluids move, but they are not linear and often give answers that depend on the starting point and the boundaries. Modeling fluid behavior is challenging due to the inherently chaotic and unpredictable character of fluid dynamics. To deal with unknown or uncertain values in this research, we used neutrosophic logic to look at the Navier-Stokes equations in a new way. Neosophic logic permits the existence of values that are partially true and partially false; …

A Novel Neutrosophic Decision-Making Approach For Optimizing Metaverse Headphone Design: Balancing Technical Performance And User Emotional Needs, Mai Mohamed, Amira Salam, Karam Sallam, Bilal Arain

Neutrosophic Systems with Applications

The concept of the metaverse, which combines various technologies to create a wide range of virtual experiences, has gained significant popularity in recent years. To fully engage in these metaverse environments, users rely on access devices such as virtual reality (VR) headsets and smartphones for augmented reality (AR). These devices must be lightweight, compact, and user-friendly to ensure comfort and enhance customer satisfaction. There is a growing focus on innovating and designing products that not only meet technical requirements but also address the emotional needs of users, ultimately improving the overall experience. Selecting the ideal design for Metaverse headphones is …

Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita

Neutrosophic Systems with Applications

Graph Theory is a branch of mathematics dedicated to studying graphs, which depict relationships between objects through vertices and edges. A significant focus in this field is the study of contact graphs, where vertices correspond to sets, and edges represent intersections between those sets. To better model uncertainties in real-world situations, several graph types---such as fuzzy, neutrosophic, and Plithogenic graphs---have been developed. This paper investigates the concept of contact graphs within these frameworks, offering insights into their behavior under various uncertain conditions.

Balancing Privacy And Security: A Comparative Analysis Of Ai-Driven Surveillance In The Uae And Usa, Belal Alghafri, Abdallah Tubaishat

All Works

AI-driven surveillance has emerged as a critical tool for enhancing public safety, enabling authorities to monitor and prevent crime and terrorism more effectively. In countries like the UAE and the USA, these systems are often implemented under the pretext of national security, offering advanced methods to track potential threats. However, the increasing reliance on AI for surveillance raises significant ethical concerns about privacy and individual freedoms. The boundary between protecting citizens and infringing on their privacy becomes increasingly blurred, potentially leading to abuses of power, diminished public trust, and a pervasive atmosphere of fear. This paper explores the complex relationship …

Ontologies For Smart Agriculture: A Path Toward Explainable Ai-A Systematic Literature Review, Rima Grati, Najla Fattouch, Khouloud Boukadi

All Works

Smart agriculture has grown significantly over the last few years, particularly with the integration of advanced technologies (e.g., the Internet of Things, robots, artificial intelligence, etc.), leading to the development of intelligent agricultural systems. However, these systems often lack data integration, interoperability, and semantic explainability. Various approaches have been proposed to address these challenges. This study provides a comprehensive literature review that addresses, on the one hand, the use of semantic resources (e.g., semantic web technologies and ontologies) to tackle data integration and interoperability in smart agriculture systems and, on the other hand, the integration of explainable artificial intelligence into …

Trenching And Compost Sustain Grain Yield Increases Over Nine Years On Deep Sands But At A Cost, David J.M. Hall, Tom J. Edwards

Grain and Other Field Crops Research Articles

Context. Crops grown on deep sands on the south coast of WA are limited by soil physical and chemical properties including compaction and poor nutrition. Aims. Crops grown on deep sands on the south coast of Western Australia are limited by soil physical and chemical properties including compaction and poor nutrition. Our aim was to determine what effects deep-placed organic amendments have on soil properties and crop production in a deep sand and whether such amendments are profitable. Methods. A long-term field trial was conducted over nine years (2015–2023) to investigate soil amendments including lime (0 and …

Automating Course Scheduling With Linear Programming And The Python Pulp Framework: First Steps, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

This article presents a pragmatic approach to automating course scheduling in an academic setting using linear programming.

We explore how linear optimization via current open-source tools can efficiently handle scheduling constraints such as instructor preferences, teaching loads, course section requirements, and specific time slots. Using Python’s PuLP library and matplotlib for visualization, we built a flexible and accessible scheduling system.

Our research prototype balances course assignments while addressing department-specific needs, demonstrating how linear programming can simplify academic scheduling and improve efficiency.

Although this is a research prototype, our results already demonstrate the ability to generate a correct course schedule that …

Ensemble Learning With Explainable Ai For Improved Heart Disease Prediction Based On Multiple Datasets

Faculty, Staff and Student Publications

Heart disease is one of the leading causes of death worldwide. Predicting and detecting heart disease early is crucial, as it allows medical professionals to take appropriate and necessary actions at earlier stages. Healthcare professionals can diagnose cardiac conditions more accurately by applying machine learning technology. This study aimed to enhance heart disease prediction using stacking and voting ensemble methods. Fifteen base models were trained on two different heart disease datasets. After evaluating various combinations, six base models were pipelined to develop ensemble models employing a meta-model (stacking) and a majority vote (voting). The performance of the stacking and voting …

An Intercomparison Of Wall Fluxes In A Turbulent Thermal Convection Chamber: Direct Numerical Simulations And Wall-Modeled Large-Eddy Simulations Enhanced By Machine Learning, Aaron Wang, Silvio Schmalfuß, Kamal Kant Chandrakar, Hadi Zanganeh Kia, Fan Yang, Mikhail Ovchinnikov, Raymond A. Shaw, Yunsoo Choi

Michigan Tech Publications

Thermal convection in a closed chamber is driven by a warm bottom, a cold top, and side walls at various temperatures. Although wall fluxes are the source of convection energy, accurately modeling these fluxes (i.e., the wall model) is challenging. In large-eddy simulations (LESs), many wall models are traditionally derived from the canonical boundary layer, which may be unsuitable for thermal convection bounded by both horizontal and vertical walls. This study conducts a model intercomparison of dry convection in a cubic-meter chamber using three direct numerical simulations (DNSs) and four LESs with different wall models. The LESs employ traditional wall …

Digital Thread: Bridging Macro–Micro Services In System-Of-Systems, Joshit Mohanty

Graduate Student Government Association Research Conference

Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.

This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the …