Digital Commons Network^™

The Effect Of Phosphate Fertilizer And Organic Matter On Phosphorus Status, Ph, And Cabbage Yield In Andisols, Mahfud Arifin, Emma Trinurani Sofyan, Anni Yuniarti, Rina Devnita, Sastrika Anindita

Jurnal Kultivasi

Andisols are characterized by high phosphorus (P) retention, which often limits P availability for crops. This study aimed to analyze the independent and interactive effects of P fertilizer and organic matter (i.e. manure and rice straw compost) on P retention, total P, available P, P uptake, soil pH, and cabbage yield. This research was conducted in pot experiments in plastic house, applying P fertilizer (0, 90, 180, 270 kg ha-1) and organic matter (20 kg ha-1 of chicken, sheep, cow manures and rice straw compost) on Andisols planted with cabbage. The experiment used a factorial randomized design. The results showed …

Health Implications Of Heavy Metal Contamination In Commercially Available Deodorant And Antiperspirant Products Sold In Benghazi, Libya, Maysson Yaghi, Khaled Elsherif

Al-Bahir

The extensive usage of deodorants and antiperspirants raises concerns about the potential health risks posed by heavy metal content. This study quantified the levels of five heavy metals: Aluminum, Zirconium, Lead, Cadmium, and Chromium in 22 commercial products widely used in Benghazi, Libya, and assessed the associated health risks. Samples, categorized into gel, stick, and roll-on formulations, were analyzed using iCAP TQ ICP-MS. Al and Zr showed the widest concentration ranges, reflecting their intentional use as active ingredients. Al levels ranged from trace amounts (0.032 mg/kg) up to a maximum of 99.10 mg/kg, while Zr was found exclusively in gel …

Application Of Augmented Reality Technology As A Dietary Monitoring And Control Measure Among Adults: A Systematic Review, Gabrielle Victoria Gonzalez, Bingjing Mao, Ruxin Wang, Wen Liu, Chen Wang, Tung Sung Tseng

School of Public Health Faculty Publications

Background/Objectives: Traditional dietary monitoring methods such as 24 h recalls rely on self-report, leading to recall bias and underreporting. Similarly, dietary control approaches, including portion control and calorie restriction, depend on user accuracy and consistency. Augmented reality (AR) offers a promising alternative for improving dietary monitoring and control by enhancing engagement, feedback accuracy, and user learning. This systematic review aimed to examine how AR technologies are implemented to support dietary monitoring and control and to evaluate their usability and effectiveness among adults. Methods: A systematic search of PubMed, CINAHL, and Embase identified studies published between 2000 and 2025 that evaluated …

Rapid Kinetic Fluorogenic Quantification Of Malondialdehyde In Ground Beef, Keshav Raj Bhandari

Theses and Dissertations

Presented herein is rapid kinetic fluorogenic method to quantify malondialdehyde (MDA) in ground beef, utilizing 2-thiobarbituric acid (TBA) as the fluorogenic probe. This assay significantly shortens the total analysis time, from sample preparation to data acquisition, to just six minutes presenting a major advancement over traditional methods that typically require two hours and multiple instruments. The assay’s robustness against matrix interferences was validated using sample volume variation and standard addition calibration methods. Additionally, the effects of ambient exposure to air, washing, and cooking on MDA content in raw ground beef were quantified. While both ambient exposure to air and cooking …

The Effects Of Nanobubble Fertigation And Soil Conditioners To Improve Nutrient Dynamics, Soil Microbial Activity, And Chili Productivity, Betty Natalie Fitriatin, Euis Ahah Rokayah, Elsa Naila Elmyra, Tualar Simarmata, Nicky Oktav Fauziah, Hanif Fakhrurroja

Jurnal Kultivasi

Drip fertigation is a fertilization method that integrates nutrient delivery with an irrigation system, which is capable of optimizing the direct delivery of nutrients to the root zone. This experiment aims to investigate the effect of drip fertigation with nanobubble technology, and soil conditioners on the population of Phosphate-Solubilizing Bacteria (PSB) and Azotobacter spp., available phosphorus, total nitrogen, growth, and yield of red chili. The study used a Strip Plot Design with two factors and three replications. The first factor was nutrient application (solid NPK fertilizing as control; drip fertigation; and drip fertigation with nanobubble technology), and the second factor …

Investigating The Effect Of Kcl Stress In Raphanus Sativus, Mason P. Oelke

ATU Honors Projects

Potassium is an essential macronutrient for plant growth and development, yet excessive potassium fertilization can induce salt stress with detrimental consequences for crop productivity and nutritional quality. Despite its agricultural relevance, potassium chloride induced stress remains significantly understudied compared to classical sodium-based salinity. This thesis investigates the physiological, biochemical, and molecular responses of Raphanus sativus to KCl stress using an integrated approach that combines germination assays, mineral profiling, and gene expression analysis.

Radish seeds were exposed to increasing KCl concentrations (0–400 mM) with or without melatonin, TEA, or EDTA. Germination percentage, fresh and dry biomass, and early seedling vigor were …

Macroscopic And In-Situ Atr-Ftir Spectroscopic Studies Of Metformin Adsorption On Soil, Maheen Mehnaz

Tennessee State University Alumni Theses and Dissertations

Emerging contaminants might pose serious threats to the soil and water environment. Metformin, an emerging micropollutant, is one of the most widely used drugs for type-2 diabetes treatment. However, its waste disposal through human excretion is causing environmental concern to the soil and water environment. Yet, knowledge about the interaction mechanism of metformin with soil remains very limited. In this study, we evaluated metformin adsorption mechanisms on model oxide minerals (gibbsite, hematite) and two Tennessee soils (Milan Loring soil and Cheatham County soil) and in the presence of soil micronutrient (molybdenum) using in situ attenuated total reflectance Fourier transform infrared …

Exploring The Potential Of Martian Agriculture: Assessing Viability And Nutritional Composition Of Plants Cultivated In Martian Regolith, Abigail Ross

Honors Theses

In addition to sunlight and water, plants can utilize a small number of nutrients from the soil to biosynthesize all the materials that are needed for growth and development. However, plants require an environment where they are able to obtain those nutrients, such as iron, magnesium, potassium, sulfur, and nitrogen. Environmental factors determine the types and accessibility of nutrients available to plants. Plants then take up these nutrients from the soil to aid in biological mechanisms and the synthesis of important molecules needed for growth and development. Ascorbic acid, commonly known as Vitamin C, is a vital molecule that is …

Full Issue, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Privacy Preserving-Based Artificial Intelligence For Precision Agriculture, Partha P. Sengupta

Dissertations

The research work finds a solution to precision agriculture of cotton cultivation using artificial intelligence (AI) models. Two sets of model performance based on the application are selected namely a low resource and a high resource setting. This is because using drone surveys to capture images identifying the classes of stressed and unstressed cotton plantation requires limited model architecture and CPU based computation. Thus, traditional AI models were selected for low resource settings. Again, for high computation intensive models like transfer learning-convolution neural network (CNN) based architectures were grouped into high resource settings. There was another issue of class imbalance …

An Integrated Modeling Framework To Evaluate Circularity Of The Corn–Water–Ethanol–Beef Nexus, Heydi Han

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation examines the transition from conventional linear agricultural and food bioenergy systems toward more circular, resilient, and resource-efficient configurations. Prior research indicates that spatial and temporal variability in soil, weather, animal biological responses, and management decisions strongly influences productivity, nutrient-use efficiency, and profitability. Studies have also shown that a diversified circular system can buffer these sources of variability, improving stability and adaptive capacity. Building on these insights, the central focus of this work is to develop an integrated modeling framework to evaluate circularity within the Corn-Water-Ethanol-Beef (CWEB) nexus and explore how climate variability and management choices shape system-wide performance. …

A Generational Analysis Of Psychological Motivators Influencing Seafarer Retention, Perisah Tahanci

The Plymouth Student Scientist

Seafarer retention is a growing concern amid increasing global demand for skilled maritime officers. This study investigates the generational differences in psychological motivators influencing seafarer retention, where ‘psychological motivators’ encompass the cognitive factors, including mental and physical wellbeing, work-life balance, compensation, working conditions, and external factors, that shape retention intentions. A cross-sectional survey (n=214) combined quantitative and qualitative analyses to systematically assess how the perceived importance and experience of these factors vary across Generation Z, Millennials, Generation X, and Baby Boomers.

The findings reveal that significant generational differences exist across most factors, particularly in work-life balance and mental wellbeing, in …

Seagrass Preference Among Pinfish In The Lower Laguna Madre, Nathaniel Garza

Theses and Dissertations

Pinfish (Lagodon rhomboides) is a common estuarine fish species found from Massachusetts to the Yucatan, Mexico. As juveniles, pinfish spend a significant portion of their life in coastal seagrasses which provide both shelter from predators and food. Along the Texas coast, there are three major species of seagrass- turtle grass (Thalassia testudinum), manatee grass (Syringodium filiforme) and shoal grass (Halodule wrightii) that differ in structural complexity. The goal of this study was to determine if pinfish associate more with one seagrass species than the others. A year-long field study was completed using twelve sample sites in the Lower Laguna Madre, …

Population Structure Of Red Drum (Sciaenops Ocellatus (Linnaeus, 1766)) In Two Systems In The Northwestern Gulf Of Mexico, Sandra Antonia Leal

Theses and Dissertations

Red drum (Sciaenops ocellatus) are an economically significant species of fish inhabiting the Gulf of Mexico. There are limited studies assessing S. ocellatus population structure focused on the southern coast of Texas. A total of 1,008 fish were collected over one year on a quarterly basis at South Bay (SB) and Holly Beach (HB) in the Lower Laguna Madre (LLM) of Texas to assess population structure. Juvenile S. ocellatus utilize the water systems of the LLM as a nursery ground and were more abundant at SB (n = 718) than HB (n = 290). The most abundant age classes were …

Isolation, Chemical Characterization, And In-Vitro Cytotoxic Evaluation Of Novel Polar Flavonoids From Chromolaena Leivensis, Matthew Tohatsu Tetteh

Electronic Theses and Dissertations

This study focuses on isolation, chemical characterization, and in-vitro cytotoxic evaluation of novel polar flavonoids from chromolaena leivensis. A 95% ethanolic extract of c. leivensis shipped by Prof. Ruben Torrenegra from University of Applied and Environmental Sciences, Bogota, Colombia, was dissolved in 1:1 methanol/chloroform mixture and its purity analyzed by TLC. The sample was eluted with toluene/methanol in an increasing order of polarity on silica gel, resulting in 49 fractions labelled CLA1 to CLA49. Among these fractions, CLA10 (1) and CLA19 (2) obtained yellow and white crystals. They were analyzed by GCMS, IR, and …

Cosmetic Surgery And Physiological Disorder: You Should Talk To Someone About Your Unwinding Anxiety, Mona Muzammil, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Body dysmorphic disorder is a mental health condition in which you can't stop thinking about one or more perceived defects or flaws in your appearance — a flaw that appears minor or can't be seen by others. But you may feel so embarrassed, ashamed and anxious that you may avoid many social situations.

When you have body dysmorphic disorder, you intensely focus on your appearance and body image, repeatedly checking the mirror, grooming or seeking reassurance, sometimes for many hours each day. Your perceived flaw and the repetitive behaviors cause you significant distress and impact your ability to function in …

Error Reduction Methodology And Data Simulation For Interval Data, Ranik Christopher Jelinek

Undergraduate Honors Capstone Projects

Chronic kidney disease (CKD) is a progressive condition affecting hundreds of millions of individuals worldwide. However, clinical datasets often record continuous laboratory measurements as categorical intervals rather than precise numerical values. This interval-censored structure presents methodological challenges for standard regression-based classifiers. This study compares three strategies for handling interval-valued predictors prior to fitting a logistic LASSO model: (1) midpoint imputation, which replaces each interval with its arithmetic center; (2) ordinal encoding, which maps intervals to integer ranks; and (3) a Monte Carlo simulation approach, which repeatedly samples uniformly from each observed interval and averages predictions across replications. Using a 10-fold …

From Morphology To Machine Learning And Genomics: Understanding Phenotypic Variation In Wild Ducks, Sara Gonzalez

Open Access Theses & Dissertations

Understanding the genetic underpinning and distribution of phenotypic variation within and between divergent groups is core towards shedding light into how populations diverge and adapt, as well as how hybridization breaks or builds on these scenarios; and thus, central to evolutionary biology. In wild organisms, however, quantifying and linking phenotypic traits to underlying genetic processes, like mutation, gene expression, epigenetics and allele interactions, remains challenging. This difficulty arises from the complex interplay between morphology, environment, and gene regulation, as well as the logistical barriers of collecting and standardizing large-scale data across individuals and populations. As a result, researchers are increasingly …

Algebraic Approach To Data Processing: Techniques And Applications, Julio Urenda

Open Access Theses & Dissertations

In many areas of human knowledge, symmetries and invariances play an important role. In fundamental physics, starting with Relativity Theory, new physical theories have been formulated in terms of invariances and of the corresponding transformation groups – i.e., in terms what a mathematician would call an algebraic approach. In engineering, devices like wind tunnels, which are based on scale-invariance, enable us to test smaller-scale models of the actual designs. In biological sciences, symmetries and invariances are extremely important in analyzing the shape and functioning of living beings, from mammals to viruses. Invariance and symmetry – in the form of fairness …

Large Language Models (Llms) For Clinical Note Generation: International Classification Of Disease (Icd) Code, Knowledge Graph (Kg) And Prompt Evaluation, Ivan P. Makohon

Computer Science Theses & Dissertations

In the past decade, a surge in the amount of electronic health record (EHR) data in the United States occurred, driven by a favorable policy environment created by the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 and the 21st Century Cures Act of 2016. Clinical notes for patients’ assessments, diagnoses, and treatments are captured in these EHRs in free-form text by physicians, who spend a considerable amount of time entering them. Manually writing these notes is time-consuming, increasing patient waiting times and potentially delaying diagnoses. Large language models (LLMs), such as GPT-4o, possess the ability …

Making Explanations Make Sense: Xai For Smishing Detection, Eleni Alexandra Katsarakes

Psychology Theses & Dissertations

Explainable Artificial Intelligence (XAI) is a key component of effective human-AI collaboration, particularly in high-stakes domains such as cybersecurity. While AI tools hold promise for mitigating threats such as SMS-based phishing (SMiShing), their real-world effectiveness may hinge not just on detection accuracy, but on whether users can make sense of the system’s outputs. As SMiShing attacks grow in both frequency and sophistication, so does the urgency of designing human-centered AI systems that support user decision-making under uncertainty. This study examined how four distinct AI explanation types - Normative (rule-based), Attributive (feature-based), Exemplar (case-based), and Recommendation-Only - influence user performance, confidence, …

Tannin Supplementation Alters Foraging Behavior And Spatial Distribution In Beef Cattle, Bashiri Iddy Muzzo, R. Douglas Ramsey, Kelvyn Bladen, Juan J. Villalba

Wildland Resources Student Research

Beef production on chemically uniform grass monocultures can limit nutrient synchrony and contribute to uneven pasture use. We evaluated whether supplementing tannins with bioactive plant secondary compounds improves foraging dynamics and landscape use by beef cattle grazing a meadow bromegrass monoculture in ways aligned with rangeland sustainability. Twenty-four Angus cow–calf pairs were allocated to six 3.6-ha paddocks (four pairs/paddock), randomly assigned to Control (Ctrl; n = 3) or Tannin treatment (TT; n = 3). Animals received 1 kg/cow/day of DDGs, with TT receiving an added 0.4% tannins (2:1 condensed:hydrolyzable). Grazing occurred during four 15-day periods (July– September) across two years. …

Gc-0270 Oncoboost - Hydration Monitoring Application, Blossom Madubike, Aafra Alam, Damola Ojo

C-Day Computing Showcase

Dehydration is a common and preventable complication for oncology patients, especially those undergoing chemotherapy and radiation. Side effects such as nausea, fatigue, and loss of appetite make it difficult for patients to maintain adequate fluid intake, contributing to avoidable discomfort and potential treatment disruptions. This capstone project presents Onco-Boost, a mobile hydration monitoring application designed to help adult oncology patients track daily fluid intake, recognize their intake patterns, and stay engaged in daily self-care between clinic visits. Built with React Native and Expo, and backed by Firebase for authentication and cloud data storage. Onco-Boost translates clinical hydration guidance and research …

Mobile Computer Vision Application For Agricultural Disease Detection Of Pepper Diseases Using Two-Stage Deep Learning System, Carlos Jose Estevez, Mai Dang, Ryan Bass

SMU Data Science Review

Plant diseases pose a significant threat to food security, particularly in developing countries where farmers often lack the resources and infrastructure for early detection. In nations like Mexico and the Dominican Republic, the spread of harmful plant diseases impacts key agricultural commodities, such as habanero peppers, leading to substantial yield losses. This study presents a computer vision system based on Convolutional Neural Networks (CNNs) and an object detection model (YOLO) to help farmers detect pepper diseases efficiently. The system uses a two-stage approach: YOLOv11n first detects pepper leaves in images, then a lightweight MobileNetV3Small model classifies whether the detected leaves …

Analyzing The Global Happiness Index, Victoria Hernandez, Christy W. Wachira

SMU Data Science Review

This study explores the Global Happiness Index using data compiled from the OECD and Our World in Data to identify key factors contributing to societal well-being. Six primary predictors were analyzed: GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity, and perceptions of corruption. Regression and clustering techniques were employed to uncover patterns among countries. By expanding the analytical scope beyond conventional economic and social indicators, this study helps identify new pathways for improving well-being across diverse cultural and economic landscapes. Additional variables such as perceived safety, political engagement, and values related to family and …

Latent Classification Of Time-Dependent Transition Rates In Longitudinal Binary Outcome Data, Joonha Chang, Wenyaw Chan

School of Public Health Faculty Publications

Continuous-time Markov chain (CTMC) models and latent classification methods are commonly used to analyze longitudinal categorical outcomes in medical research. While CTMC models are popular for their simplicity and effectiveness, their assumption of constant transition rates presents limitations in capturing dynamic behaviors. To address this, non-homogeneous continuous-time Markov chains (NH-CTMCs) have been developed, incorporating time-varying transition rates to enhance model flexibility. In this study, we leverage closed-form transition probabilities for a fully ergodic two-state NH-CTMC model and propose a latent class clustering approach to identify heterogeneous transition rate patterns within the population. We emphasize the potential advantages of these models …

Statistical Challenges And Simulation Results For Pilot Clinical Trials, Weiliang Cen

USF Tampa Graduate Theses and Dissertations

Background: The effect size estimated from a pilot trial is often an inaccurate reflection of the true effect size observed in a large trial, leading to either underestimation or overestimation. Published data suggest that effect sizes from large trials are typically smaller than those reported in their corresponding pilot trials. To address this discrepancy, conservative or discount adjustment methods are widely recommended to modify pilot trial effect sizes when calculating sample sizes, thereby maintaining adequate statistical power. This study aims to assess effect sizes from both pilot and large trials and to evaluate the performance of existing adjustment methods.

Methods: …

Interpretable Machine Learning For Cardiovascular Risk Prediction: Insights From Nhanes Dietary And Health Data, Md Ahiduzzaman, Md Nahid Hasan

Faculty Publications

Background: Cardiovascular diseases (CVD) are one of the leading global causes of death, which requires an accurate early prediction. This study aimed to develop transparent machine learning (ML) models using National Health and Nutrition Examination Survey (NHANES) data from 2017–2023 to predict CVD risk based on dietary and health factors.

Methods: We analyzed data from 12,382 adults (aged 18 and older) from NHANES 2017–2023, including 41 dietary, anthropometric, clinical, and demographic variables. Recursive Feature Elimination (RFE) was used to select an optimal subset of 30 predictors. To address substantial class imbalance in the outcome, we applied the Random Over-Sampling Examples …

Survival Analysis Of Breast Cancer Patients In Texas Using Classical And Machine Learning Methods, Sidketa Fofana, Tamer Oraby, Salique H. Shaham, Everardo Cobos, Manish K. Tripathi

School of Medicine Publications

Background

Breast cancer is considered one of the most common cancers in women worldwide. In this study, we used an 11-year cohort of malignant breast cancer survival data in Texas to investigate the factors that might explain why some breast cancer patients live longer than others.

Methods

We performed standard survival analyses, including generating Kaplan‒Meier survival curves, using the log-rank test, and applying Cox proportional hazards regression to identify the unique features of breast cancer patients and determine the main factors influencing long-term survival. We also conducted a Random Survival Forest analysis for classification and prediction. Finally, we used Mahalanobis …

Circulating Levels Of Insulin-Like Growth Factor I (Igf-I) And Risk Ofmultiple Myeloma: An Observational And Mendelian Randomisation Study, Yolanda Benavente, Sara Hermosa, Nikos Papadimitriou, Alyssa I. Clay-Gilmour Ph.D., Elizabeth E. Brown, Jonathan N. Hofmann, Nathaniel Rothman, Qing Lan, Sonja I. Berndt, Demetrius Albanes, Mark Purdue, Mitchell J. Machiela, Stephen J. Chanock, Parveen Bhatti, Wendy Cozen, Aaron Norman, Susan L. Slager, James R. Cerhan, Vincent Rajkumar, Shaji J. Kumar, Et. Al.

Faculty Publications

Evidence for an association between insulin-like growth factors (IGF) and multiple myeloma (MM) is inconsistent. We examined total IGF-I concentrations and risk of MM by combining baseline serological data among UK Biobank participants (n = 444 187; 732 incident MM) with a two-sample Mendelian randomisation (MR) analysis using identified genetic variants associated with circulating total IGF-I and IGF-binding protein 3 (IGFBP-3) in the InterLymph consortium (2434 MM and their 2567 controls). Finally, additional lymphoid neoplasm (LN) subtypes were included for comparison with the main hypothesis. Circulating IGF-I level was positively associated with MM risk Hazard ratio-HR-per one standard deviation-SD-increase …