Digital Commons Network^™

Antibacterial Potential Of Tapanuli Orangutan (Pongo Tapanuliensis) Food In Batang Toru Forest Against Escherichia Coli And Salmonella Typhi, Herna Febrianty Sianipar, Wahyu Widoretno, Luchman Hakim, Rezi Rahmi Amolia, Fatchiyah Fatchiyah

Karbala International Journal of Modern Science

Diarrhea is a common disease affecting orangutans, primarily caused by Escherichia coli and Salmonella typhi bacteria. To treat this disease, antibacterial food sources are essential as therapeutic agents for orangutans. The fruits consumed by Tapanuli orangutans include Campnosperma auriculatum, Agathis borneensis, Artocarpus heterophyllus, Castanopsis argantea, and Aglaia tomentosa. This study aims to examine the amino acid and phytochemical components with potential antibacterial properties in these five fruit species and their inhibitory effects on E. coli and S. typhi growth through cell lysis, observed using a Scanning Electron Microscope (SEM). The samples were tested for amino acids, phytochemicals, vitamin C content, …

Study Of Anomalous Variations In Seismic And Non-Seismic Parameters Using Machine Learning Techniques To Develop The Earthquake Forecasting Model In The Himalayan Belt, Senthil Kumar M

Theses and Dissertations

Understanding and forecasting earthquakes is not just about science it’s about saving lives, even as the dynamic and hidden nature of Earth's tectonic processes makes this an intricate challenge. The Himalayan belt is one of the most seismically active regions globally due to the collision of the Indian and Eurasian tectonic plates. Investigating this region is essential for understanding highly complicated tectonic mechanisms and reducing substantial hazards posed to millions of people by persistent and intense seismic events. This study aims to enhance forecasting methodologies by applying machine learning techniques while dealing with the inherent challenges of geological complexity and …

Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud

Karbala International Journal of Modern Science

The food sector must contend with issues such as pathogen resistance to some of the available chemical agents, environmental pollution, and climate change to provide healthy food for livestock and people. The application of atmospheric pressure plasma jets (APPJs) is one potential solution for such problems. Plasma is appropriate for effective surface decontamination regarding food products and seeds, surface decontamination, and achieving improved agricultural production yields. The impact of plasma-activated water (PAW) produced by plasma jet discharge (PJD) system on in vitro-cultivated wheat seeds is examined in this work. For this aim, a plasma jet system was constructed with a …

Analytical Solution And Stability Of Ψ-Prabhakar Delayed Systems: Application To Antibiotic Production, Mustafa Aydin

Turkish Journal of Mathematics

The analytical solution of the linear ψ -Prabhakar delay differential equations is explored using the method of variation of parameters, in which a ψ -general delayed exponential matrix function is introduced. The ψ -Prabhakar calculus is enhanced in terms of the semi-group property, inversion results, and several simplified calculations and relations. The system's stability is analyzed within the framework of Ulam-Hyers stability. Finally, the theoretical findings are validated through an application to antibiotic production.

On The Solutions Of Difference Equations Of The Volterra Type, Hakan Adigüzel

Turkish Journal of Mathematics

In this paper, we conduct a thorough analysis of the qualitative behavior of solutions to three different types of difference equations of the Volterra type. Utilizing the principles of discrete calculus and various well-known inequalities, we have presented our findings. To conclude our theoretical findings, we provide several examples that illustrate full alignment with the findings.

Design And Investigation Of Triarylamine Functionalized Luminophores For Multi-Functional And Stimuli-Responsive Applications, Sasikala R

Theses and Dissertations

Organic solid-state fluorescent materials have garnered attention over many decades in virtue of their contribution in the development of LED devices and biomedical applications. Nevertheless, the potential of fluorescent molecules in device applications was underused due to aggregation-caused quenching (ACQ) effect. The ACQ effect commonly quenches the organic molecules fluorescence intensity in the aggregated or condensed state, which can significantly influence their performance in practical applications.

The organic polyaromatic fluorophores exhibit strong fluorescence in the solution state. After culmination of years of work, Prof. Tang’s research group discovered a new phenomenon of aggregation-induced emission (AIE) in the fluorescence molecules constructed …

Digital Identity Management As A Critical Criminal Justice And Homeland Security Legal Issue: A Qualitative Analysis Of The Reasonable Person Factors Involved In Court Decisions, William H. Nicholson

Doctoral Dissertations and Projects

The purpose of this descriptive qualitative applied study is to define and explain through analysis the reasonable person standard as it relates to prosecution and sentencing computer crime cases involving digital identities while addressing the problem of digital anonymity. This has been done by analyzing computer crime cases with the advent of current and planned technologies, and surveying potential jurors to understand the current state of knowledge of digital attribution. This descriptive qualitative research method analyzed the problem through the use of criminological theories of control and social learning theory to better understand the reasonable person standard in computer crime …

Securing Ai-Generated Code, Andreas E. Nelson

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

The increasing use of AI for code generation presents significant security challenges, as these tools often lack inherent security awareness and can produce vulnerable code. This paper investigates these security risks, outlining common types of vulnerabilities (such as injection flaws and improper resource handling) found in AI-generated code. It further explores and evaluates mitigation techniques aimed at im-proving code security, including model fine-tuning and adversarial strategies like Security Verifier Enhanced Neural Steering (SVEN). Findings indicate that while current methods offer promising ways to reduce vulnerabilities, ongoing research and development are crucial for the secure and responsible deployment of AI in …

A Comprehensive Deep Learning System With Mgrf Modeling For Predicting Breast Cancer Response To Neoadjuvant Chemotherapy, Ahmed Sharafeldeen, Fatma Taher, Norah Saleh Alghamdi, Eman Alnaghy, Reham Alghandour, Khadiga M. Ali, Sameh Shamaa, Abdelrahman Gamal, Mohammed Ghazal, Sohail Contractor, Ayman El-Baz

All Works

Accurate prediction of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) is critical for tailoring treatment strategies and improving patient outcomes. This study introduces a novel deep learning-based framework that integrates multi-parametric magnetic resonance imaging (MRI) (i.e., T1, T2, STIR, and DWI), along with clinical and molecular subtype markers, to classify tumor response into pathological complete response (pCR), partial response (PR), and stable disease (SD). First, tumor regions are delineated across MRI modalities and then modeled using a translation-invariant Markov-Gibbs random field (MGRF) with analytical parameter estimation to capture modality-specific spatial appearance patterns correlated with NAC response. Subsequently, diffusion-weighted MRI …

A Model Intercomparison Study Of Aerosol-Cloud-Turbulence Interactions In A Cloud Chamber: 1. Model Results, Sisi Chen, Steven K. Krueger, Piotr Dziekan, Kotaro Enokido, Theodore Macmillan, David Richter, Silvio Schmalfuß, Shin Ichiro Shima, Fan Yang, Jesse C. Anderson, Will Cantrell, Dennis Niedermeier, Raymond Shaw, Frank Stratmann

Michigan Tech Publications

This study presents the first model intercomparison of aerosol-cloud-turbulence interactions in a controlled cloudy Rayleigh-Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber-averaged statistics of microphysics and thermodynamics in a warm-phase, cloudy environment under steady-state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet …

Strengthening Scientific Integrity: Digital Forensics For Biomedical Research Imaging, João Phillipe Cardenuto, Daniel Moreira, Anderson Rocha

Computer Science: Faculty Publications and Other Works

To fight against the increasing misconduct cases in science, this Ph. D. research confronted the challenge of scientific integrity with a pioneering investigation into digital forensic analysis specifically tailored for biomedical images. This work conducted extensive research into key manipulation types–copy-move forgery, image reuse, and AI-generated content–developing novel, fully explainable, and auditable computational detection methods for each. In a commitment to transparency and to promote research to the area, these techniques are provided as open-source resources. Besides the isolated techniques for each type of image forged, a central contribution is the development of an end-to-end system, created through collaboration with …

A Cancer Education Needs Assessment: Informing Middle-Aged Female Patients About The Relationships Between Obesity And Women’S Health Concerns In The Reproductive System, Breast, And Endometrial Health, Batul Mirza

MUSC Theses and Dissertations

Obesity significantly impacts women’s health, particularly among middle-aged women, by increasing the risk of hormone-sensitive cancers such as breast, endometrial, and reproductive system cancers. This study examines the educational needs of this demographic group regarding obesity-related cancer risks and explores effective intervention strategies. Obesity-induced mechanisms – hormonal imbalances, chronic inflammation, and insulin resistance – drive cancer susceptibility, emphasizing the need for targeted health education. The study employs a qualitative design, which includes interviews with subject matter experts (SMEs) and surveys of middle-aged women. The goal is to assess awareness, perceived barriers, and preferred learning methods. Findings suggest that with many …

Secondary Malignancies In Patients With Meningioma: A Surveillance, Epidemiology, And End Results Data Analysis, Maxwell W. Pickles, Thomas Z. Rohan, Shreya Vinjamuri, Nikolaos Mouchtouris, Roger Murayi, David P. Bray, James J. Evans

Department of Neurosurgery Faculty Papers

BACKGROUND: The risk of secondary primary malignancies (SPMs) in meningioma patients is not well understood. In this unidirectional analysis, we evaluated the risk of SPMs occurring following a primary diagnosis of meningioma.

METHODS: The Surveillance, Epidemiology, and End Results (SEER-17) database (2000-2020) was used to identify 124,769 meningioma patients from a total of 9,208,295 cancer cases. Standardized incidence ratios (SIRs) were calculated using SEER's statistical analysis package to evaluate SPM risk. Basic demographic and treatment information was collected as well.

RESULTS: Of the 124,769 patients, 11,411 (9.2%) received diagnoses of an SPM, which correlates to a higher risk than the …

Limited Soil Water Recharge In Summer Affects Seasonal Isotopic Signatures Of Tree Xylem Water, Marius G. Floriancic, Gregory R. Goldsmith, Harsh Beria, Scott T. Allen, James W. Kirchner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Recent studies have reported that xylem waters in forest trees during the summer growing season are often isotopically similar to winter, rather than summer, precipitation. Several hypotheses have been proposed to explain this observation, which can be viewed as a form of ecohydrological separation, but empirical tests spanning space and time remain limited. We hypothesise that variations in the seasonal origin of precipitation found in tree xylem waters can be explained by seasonal differences in soil water recharge. We test this hypothesis by evaluating to what extent climatic aridity can explain seasonal signals in extensive surveys of the isotope ratios …

Spatiotemporal Responses To A Rural Highway By Four Mammal Species, Caitlin K. Brett, Anna Rose Mehner, John H. Young Jr., Sarah E. Lehnen, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

Roads can negatively impact the wildlife communities they transect. Road mortalities from wildlife-vehicle collisions are one direct effect, but roads may also indirectly affect wildlife behavior, movement, or local distribution. Quantifying the spatial extent of these road-effects is important for understanding how roads indirectly affect species of concern, identifying potential sources of disturbance, and for estimating the effectiveness of road mitigation structures. Farm-to-Market Road (FM)106, which transects part of the Laguna Atascosa National Wildlife Refuge in Cameron County, Texas, has been identified as a potential source of wildlife road mortalities, particularly for one of the two remaining breeding populations of …

A Rapid Method For Identifying Plant Oxidative Stress And Implications For Riparian Vegetation Management, Mizanur Rahman, Takashi Asaeda, Kiyotaka Fukahori, Md Harun Rashid, Hideo Kawashima, Junichi Akimoto, Refah Tabassoom Anta

School of Earth, Environmental, & Marine Sciences Faculty Publications

Native and invasive plants of the riverain region undergo a range of environmental stresses that result in excess reactive oxygen species (ROS). Hydrogen peroxide (H2O2) is a relatively stable and quickly quantifiable way among different ROS. The herbaceous species including Artemisia princeps, Sicyos angulatus, and Solidago altissima were selected. The H2O2 and photosynthetic pigment of leaves were measured, soil samples were analyzed to quantify macronutrients such as total nitrogen (TN), total phosphorus (TP), and soil moisture, and photosynthetic photon flux density (PPFD) was also recorded at different observed sites of Arakawa Tarouemon, Japan. The H2O2 concentration of S. altissima significantly …

The Response Of Mitochondrial Position To Glucose Stimulation In The Min6 Model System, Luis Perez

Arts & Sciences Graduate Student Theses and Dissertations

The compartmentalization of eukaryotic cells into membrane-bound organelles with specific subcellular positioning enables precise spatial and temporal control of cellular functions. While functionally significant mitochondrial localization has been demonstrated in cells such as neurons, it remains unclear how general these cell principles are. Here, we examine the spatial organization of mitochondria within MIN6 pancreatic beta cells under variable glucose conditions. We observe glucose-dependent redistributions of mitochondria, favoring peripheral localization at elevated glucose levels when insulin secretion is also elevated. Our results suggest that active mitochondrial transport along microtubules and calcium activity, but not ATP synthesis, are critical regulators of this …

Post-Wildfire Erosion And Sedimentation: An Escalating Threat For Utah Fisheries, Colton James, Kendall Becker, Scott Hotaling, Aish Chandrasekaran, Alex Fiedler, Timothy E. Walsworth, Patrick Belmont

All Current Publications

Wildfires are a natural part of the western U.S. landscape and provide numerous benefits, including enhanced nutrient cycling and habitat rejuvenation. Utah’s fish populations evolved with wildfire as a common disturbance. However, the increasing size and severity of wildfires, combined with Utah’s heavily engineered and fragmented stream networks, pose a contemporary risk to fish populations. This fact sheet reviews wildfire impacts on erosion and Utah's watersheds and fisheries. It outlines measures we can take to prevent post-wildfire fish die-offs.

Synthesis Of Cancrinite Zeolite From Toraja Natural Bentonite For Heavy Metal Removal From Wastewater, Yuli Astuti, Paulina Taba, Siti Fauziah, Syarifuddin Liong, Yusafir Hala, Nur Umriani Permatasari, Satria Putra Jaya Negara, Fadliah Fadliah

Karbala International Journal of Modern Science

This study explores the production of cancrinite (CAN) zeolite from bentonite found in Toraja (a place in South Sulawesi Province, Indonesia) and its effectiveness in removing Pb²⁺ and Fe³⁺ ions from wastewater. The synthesis was carried out using a hydrothermal method with varying NaOH concentrations, where a single phase of zeolite was formed at 5 M, as confirmed through XRD analysis. FTIR results showed the characteristics of CAN zeolite with typical absorption peaks at 676, 622, and 565 cm^-1, as well as the presence of carbonate groups (CO₃^2-) at 1300-1400 cm^-1. SEM …

Machine Learning Crime Prediction Models And The Gap Between Research And Implementation: A Systematic Review, Ricardo Huamantingo, Miguel Cano-Lengua, Ciro Rodriguez

Karbala International Journal of Modern Science

A crime is an illegal or violent act committed by one individual against another. The increasing crime rate has become a major concern as it negatively affects people's quality of life and generates significant social and economic costs. This study aims to identify the most widely used machine learning (ML) models for crime prediction, determine evaluation metrics for assessing model performance, and analyze key data characteristics to enhance real-world implementation. The study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A search string was formulated using the population, intervention, comparison, and outcomes (PICO) framework and applied …

Psilostachyin B As Potential Immune Checkpoint Inhibitor Targeting Ctla-4 And Pd-L1 In The Development Of Cancer Immunotherapy: A Computational Investigation, Moh Dliyauddin, Nabila Shafa Yumna Salsabila, Noviana Dwi Lestari, Sapti Puspitarini, Mansur Ibrahim, Sri Rahayu, Muhammad Sasmito Djati, Muhaimin Rifa’I

Karbala International Journal of Modern Science

Immunotherapy is a promising treatment approach by targeting immune checkpoints such as CTLA-4 and PD-L1 to overcome cancer progression. The utilization of Curcuma longa and Phyllanthus niruri as potential immune checkpoint inhibitors offers an alternative cancer therapy. Computational analyses including molecular docking and molecular dynamics with validation using Molecular Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA), Dynamic Cross-Correlation Matrix (DCCM), and Principal Component Analysis (PCA), were performed in this study. Results show that Psilostachyin B is the most promising inhibitor candidate against CTLA-4 and PD-L1, with binding affinity values of -6.9 and -6.8 kcal/mol, respectively. Molecular dynamics simulation results indicated that Psilostachyin B …

Making And Breaking Chaos: Analog Computer Implementation Of The Lorenz Model, Reed Lefevre, James Doyle

Macalester Journal of Physics and Astronomy

Hybrid analogue-digital computers have been shown to have certain advantages over traditional digital computers when solving nonlinear partial differential equations. Motivated by this fact, we implement the Lorenz equations on an analogue electronic computer and vary the parameters to analyze the bifurcations. With the working circuit, we compared experimental results to various digital simulations to assess the effectiveness of our circuit. We find clear qualitative agreement between the physical circuit and digital simulations; however, we observe a noticeable quantitative difference in behavior. The circuit depicts a picturesque Lorenz Butterfly plot and bifurcates into fixed points and chaos; however, these bifurcations …

"...Anything My Friend Shares, I Would Want To Support Them By Clicking On It": Co-Designing Story-Based Interventions Against Clickbait For Teenagers, Ankit Shrestha, Audrey Flood, Bryson Hackler, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Teenagers' lack of digital sophistication and cyber hygiene makes them vulnerable to social engineering attacks, especially as they start using social media. Clickbait, one of such attacks, is primarily performed through social media to trick users into clicking on malicious links. With teenagers' increasing use of social media, clickbait poses a substantial threat to their online safety. The existing online safety measures for teens mainly focus on parental mediation, which can be perceived as restrictive and privacy-invasive. To this end, researchers recommended empowering teens to deal with online risks. In order to design such interventions for clickbait, we conducted co-design …

Dose Characterization Of Galactic Cosmic Rays In The Human Brain: A Phits-Based Study With A Segmented Anatomical Phantom, Shanice N. Manning

LSU Master's Theses

Astronauts aboard the International Space Station (ISS) are chronically exposed to a complex space radiation environment composed of galactic cosmic rays (GCR), solar particles, and Earth's trapped radiation. These high-energy particles interact with spacecraft shielding, producing secondary particles that can penetrate inside and deposit energy in sensitive tissues. Although animal studies have been useful in assessing space radiation risks, anatomical and physiological differences limit their applicability to human anatomy especially neuroanatomy. To address this gap, we developed a computational framework to model radiation dose distribution within the human brain using Monte Carlo simulations in Particle and Heavy Ion Transport code …

Hyperspectral Band Selection Via Heterogeneous Graph Convolutional Self-Representation Network, Junde Chen, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hyperspectral image (HSI) band selection (BS) plays a crucial role in HSI dimensionality reduction, aiming to identify a representative subset of bands with minimal redundancy. However, conventional BS approaches primarily operate in the Euclidean domain, often overlooking the structural characteristics of pixels and spectral bands, such as spatial continuity and spectral dependencies. In addition, they handle each HSI as an integrated unit to harness implicit spatial information, disregarding spatial distribution variations across different homogeneous regions. To fully leverage structural information, this study introduces a novel BS method, termed the dual heterogeneous graph convolutional network with enhanced self-representation (ESR-HGCN), for HSI …

Research And Education In Robotics: A Comprehensive Review, Trends, Challenges, And Future Directions, Mutaz Ryalat, Natheer Almtireen, Ghaith Al-Refai, Hisham Elmoaqet, Nathir Rawashdeh

Michigan Tech Publications

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is …

A Study Of Machine Learning Techniques In Solving Biochemical And Chemical Problems, Kenneth Micheal Plackowski

Chemistry and Chemical Biology ETDs

Data-driven approaches to solving problems in biology and chemistry require utilization of reliable techniques and machine learning algorithms are the modern reliable approach. This work presents three problems that involve use of supervised learning techniques when classification is the goal and unsupervised learning techniques when global data representation is the goal.

In the first problem, we demonstrate the use of unsupervised clustering techniques, self-organizing maps and K-means, to ascertain analyte detection capabilities of carbon nitride dots. In the second problem, we add scalability features to a functional group classification model applied to infrared data and evaluate its ability to inform …

Nanoporous Gold Nanoparticles And Model Membrane Systems Applied To The Study Of Lipopolysaccharide (Lps), Dhanbir Lingden

Dissertations

Lipopolysaccharide (LPS), a key structural component of Gram-negative bacteria, is a major trigger of sepsis and septic shock, the systemic inflammatory conditions responsible for millions of deaths annually. Even at concentrations as low as 1 ng/mL, LPS can activate the immune system and initiate inflammatory cascades. According to the Global Burden of Disease Study 2017, sepsis accounted for 48.9 million cases globally, with 11 million deaths, emphasizing the urgent need for improved diagnostic and therapeutic strategies.

Accurate and rapid detection of LPS is vital for early intervention and improved clinical outcomes. While traditional detection methods are still widely used, modern …

How Multi-Scale Modeling Can Help Examine Social Determinants Of Health And Resulting Disparities, Kyoko Yoshida, Elsje Pienaar, Shalanda A. Bynum, Naomi Chesler, Mitchel J. Colebank, Jessie Heneghan, Nadra Tyus, Jasmine Miller-Kleinhenz, Bruce Y. Lee

Faculty Publications

Social determinants of health (SDOH) are the conditions in which people live, work, and play, and the wider set of factors (e.g., social and economic systems and policies) that shape a person’s daily life. SDOH can differ significantly across communities and populations, having positive impacts for some and negative impacts for others. Ultimately, this results in differences in health and disease distribution, that are known as health disparities. Despite the known impacts of SDOH and calls to characterize, address, reduce, and eliminate health disparities, they persist and, in some cases, have worsened. To address this challenge, a session at the …

Theoretical And Experimental Investigation Of Liquid-Liquid Phase Separation: Characterizing Elastin-Like-Polypeptides, Adam D. Quintana

Chemical and Biological Engineering ETDs

This dissertation develops and validates a semi-empirical Flory–Huggins-based interaction model, combined with Cahn–Hilliard simulations, for predicting multi-component liquid–liquid phase separation (LLPS) in elastin-like polypeptide (ELP) systems. Equilibrium droplet compositions, measured using a PDMS-based microfluidic device, enabled direct parameterization of interaction coefficients. The model was applied to generate phase diagrams and assess composition dependence in ternary mixtures. Cahn–Hilliard simulations were conducted to explore potential phase morphologies under different interfacial conditions. Multi-component Lattice Boltzmann simulations were implemented to model droplet morphology evolution under varying interfacial and diffusive parameters, reproducing experimentally relevant morphologies. A three-phase wetting study revealed conditions for selective wetting and …