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Engineering Nanomaterials From Phase-Change Biological Materials Reacting With Carbon Dioxide, Qingyang Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

The current global situation concerning CO2 emissions is increasingly alarming, with rising concentrations of CO2 significantly worsening climate change and global warming. Atmospheric CO2 levels are now at their highest in millions of years, driving a host of catastrophic effects, including but not limited to extreme weather events, rising sea levels, ocean acidification, disrupted ecosystems, deteriorating air quality, respiratory health issues, heat-related illnesses, threats to food and water security, and escalating social and geopolitical tensions. To keep global warming to no more than 1.5°C higher than that of pre-industry – as called for in the Paris Agreement – emissions need …

Electro-Mechanical Behavior Of Core-Shell Carbon Grease-Silicone Fibers Fabricated Via Coaxial Direct Ink Writing, Fahrettin Kilic

Graduate Theses, Dissertations, and Problem Reports (ETD)

Highly stretchable strain sensors are essential components in soft electronics, enabling integration of sensing and signal transmission into deformable systems. This thesis explores the fabrication and characterization of coaxial core–shell fibers composed of a conductive carbon grease core and an elastomeric silicone shell. These fibers were produced using coaxial direct ink writing (DIW), a versatile additive manufacturing technique that allows continuous deposition of multi-material filaments. The goal was to achieve mechanically compliant yet electrically stable fibers capable of withstanding large deformations, suitable for applications in wearable electronics and soft robotics.
The printed fibers were systematically examined through mechanical tensile testing, …

A Framework For Biomimetic Robot Design Applied To The Development Of A Robotic Model Of Drosophila Melanogaster, Clarissa A. Goldsmith

Graduate Theses, Dissertations, and Problem Reports (ETD)

For decades, the field of biologically inspired robotics has leveraged insights from animal locomotion to improve the walking ability of legged robots. Recently, “biomimetic” robots have been developed to model how specific animals walk. By prioritizing biological accuracy to the target organism rather than the application of general principles from biology, these robots can be used to develop detailed biological hypotheses for animal experiments, ultimately improving our understanding of the biological control of legs while improving technical solutions. Much of this work involves biologically inspired walking controllers informed by the morphology and dynamics of the insect nervous system, which necessitate …

In Vitro Comparative Study Of Composite Coatings For Magnesium-Based Bone Implants, Abdelrahman Amin, Bryce Williams, Thomas Mcgehee, Alyssandra Navarro, Vipul Patil, Mostafa Elsaadany, Hanna Ibrahim

Biomedical Engineering Faculty Publications and Presentations

This study provides a comparative assessment of the corrosion, morphology, and biological properties of four of the most promising coating methods for magnesium in biomedical applications, namely micro-arc oxidation (MAO), graphene oxide (GO)-containing MAO coating, MAO/sol-gel composite coating, and MAO/polycaprolactone (PCL) polymer dip coating approaches. Despite the abundance of research focused on these promising coating approaches, there is a notable lack of comparative studies evaluating their properties. To this end, the investigated composite coatings are ZK60+MAO, ZK60+MAO/GO, ZK60+MAO/Sol-gel, and ZK60+MAO/PCL composite coating. Several tests were used to assess various properties of the prepared groups such as in vitro corrosion characteristics, …

Finite Element Simulation Of Interstitial–Lymphatic Fluid Flow And Nanodrug Transport In A Solid Tumor: An Intratumoral Injection Approach, Gobinda Debnath, Buddakkagari Vasu, Rama Subba Reddy Gorla

Faculty Publications

Objective: This study presents a mathematical model and finite element simulations to investigate interstitial fluid flow and nanodrug transport in a solid tumor, incorporating transvascular exchange, convection–diffusion–reaction dynamics, and intratumoral injection mechanisms. Impact Statement: Optimizing nanodrug distribution remains a critical challenge in cancer therapy. The proposed model advances nanomedicine by enhancing the mechanistic understanding of nanodrug transport in a solid tumor. Introduction: Cancer, a global threat, often manifests as solid tumors driven by uncontrolled cell growth. The heterogeneous microenvironment, lymphatic drainage, nano-bio interactions, and elevated interstitial fluid pressure (IFP) hinder effective nanodrug delivery. Nanoparticle (NP)-based drug delivery systems offer a …

Interfacing Neural Models: Biocompatibility And Fabrication Of A Flexible, Self-Folding Microelectrode Array, Fernando A. Pesantez Torres

Electronic Theses & Dissertations (2024 - present)

Neurodegenerative diseases pose a formidable challenge in modern medicine, necessitating the development of advanced research tools that can elucidate their complex pathophysiology. Recent advancements in neurodegenerative disease research have led to the development of three-dimensional (3D) neurodegenerative organoids using human induced pluripotent stem cells (hiPSCs). These organoids closely mimic human brain architecture and functionality, providing a valuable tool for understanding complex diseases. Additionally, the ability to generate and study brain organoids consistently and in large quantities holds potential for a controlled in vitro setting and high-throughput drug screening. However, these models are complex systems requiring specialized maintenance, analysis, and manipulation …

Applications Of Reservoir Simulation And Machine Learning In Subsurface Energy Systems For Decarbonization, Seyedmohammadmehdi Nassabeh

Theses: Doctorates and Masters

The transition to a low-carbon future necessitates innovative approaches to carbon management and hydrogen storage, particularly in the context of enhanced oil recovery (EOR) from hydrocarbon reservoirs. This study employs advanced analytics and machine learning techniques to optimize carbon management strategies. One key focus of this research is to evaluate the effectiveness of flue gas and CO2 in Water Alternating Gas (WAG) injection within a homogeneous fractured carbonate reservoir characterized by low porosity and permeability. A computational model was developed to depict the flow regime in the reservoir and simulate reservoir fluid behavior using Eclipse (E300) software, various hybrid EOR …

Replicating The Functionality Of Ghost Knifefish Cerebellar Feedback Using Synthetic Nervous Systems, Sheldon Paul Cj Johnson

Graduate Theses, Dissertations, and Problem Reports (ETD)

Sensory inputs allow animals to perceive, react, and adapt to an environment. However, the sensory information received by the body, such as visual, auditory, and proprioceptive information, could become overwhelming, thus overloading the brain. Yet, animals can process all this information by canceling redundant signals from their surroundings, allowing them to be more sensitive to novel or unexpected signals in their environment. Each species (i.e., birds, fish, mammals) has its own way of using and filtering sensory information, from auditory to locomotion adaptivity. Cerebellar circuits contribute to sensory filtering in a variety of systems. In particular, research on Ghost knifefish …

Recovery Of Iron And Aluminum From Acid Mine Drainage For Beneficial Uses, Katelyn Renee Pepe

Graduate Theses, Dissertations, and Problem Reports (ETD)

Acid mine drainage (AMD) is a widespread issue across the globe, in which some of the most critical cases are created by the mining industry. Researchers have investigated ways to derive benefits from AMD, such as precipitating rare earth elements (REEs) to generate potential revenue from AMD treatment and supplement market demand. However, the bulk of precipitated sludge is composed of iron and aluminum, which also have market value but are discarded in current practice.

Using the Omega site in West Virginia (WV) as a representative AMD source, the objectives of this study are (1) to determine a replicable precipitation …

Evaluation Of The Dnazyme Gr5 For The Determination Of Lead Speciation In Natural Waters, Gaganprit Gill

Theses and Dissertations (Comprehensive)

This thesis explores the development and application of a DNAzyme-based biosensor designed to detect labile metal species in environmental samples. Real time and on-site monitoring of labile metal fractions would make a valuable contribution to environmental management, as these fractions are the most bioavailable and pose significant toxicity risks to aquatic organisms. Conventional methods for detecting labile metals, while effective, are often burdened by high costs, complexity, and lengthy processing times, making them less ideal for rapid and widespread environmental assessments.

The first manuscript of this thesis (chapter 2) establishes the fundamental capabilities of the Pb²⁺-specific DNAzyme GR5 …

Multi-Source Remote Sensing–Based Soil Moisture Prediction Using Machine Learning, Niraj Neupane

Electronic Theses and Dissertations

Soil moisture (SM) plays a central role in climatic and environmental processes, influencing shear strength of soil, agricultural productivity, land–atmosphere interactions, and hydrologic functioning. However, accurately estimating SM across diverse climatic regions remains challenging due to spatial heterogeneity, limited in situ measurements, and inconsistencies in sensor resolution. Machine learning (ML) and remote sensing offer promising avenues for improving SM prediction, yet many existing approaches struggle with generalization across climatic gradients and often fail to capture temporal variability. This study integrates multi-source satellite and climate datasets, including SMAP L4_SM, MODIS land surface temperature, Daymet meteorological variables, and in situ observations from …

Environmentally Friendly Chelation For Enhanced Algal Biomass Deashing, Agyare Asante, George Daramola, Ryan W. Davis, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

High ash content in algal biomass limits its suitability for biofuel production by reducing combustion efficiency and increasing fouling. This study presents a green deashing strategy using nitrilotriacetic acid (NTA) and deionized (DI) water to purify Scenedesmus algae, which was selected for its high ash removal potential. The optimized sequential treatment (DI, NTA chelation, and DI+NTA treatment at 90–130 °C) achieved up to 83.07% ash removal, reducing ash content from 15.2% to 3.8%. Elevated temperatures enhanced the removal of calcium, magnesium, and potassium, while heavy metals like lead and copper were reduced below detection limits. CHN analysis confirmed minimal …

Comparing The Sensitivity And Specificity Of Novel Motor Assessments For Traumatic Brain Injury, Paula K. Johnson, Ariana M. Hedges-Muncy, Erin D. Bigler, Lorie Richards, Steven Knight Charles

Faculty Publications

Background: Portable technology that records movements with high accuracy provides potential for sensitive clinical movement tests for individuals who experienced a traumatic brain injury (TBI). Objective: (1)To present impairments assessed using markerless motion capture (MMC) and (2) to compare the sensitivity and specificity of the MMCmediated tests to each other and to common clinical tests. Design: Screening study, using as criterion standard the ability to classify participant with TBI versus control participant. Setting: Research laboratory. Participants: The study included 30 individuals with TBI and 101 control participants. Entry criteria included most recent head injury < 5 years old, no history of movement issues prior to injury, no movement-affecting medications, and sufficient cognitive ability to follow instructions. Interventions: Not applicable. Main Outcome Measures: Performance on MMC-mediated tests and existing clinical analogs. MMC-mediated tests included finger oscillation, simple reaction time, and visually guided movement tasks. For comparison, participants also completed the following clinical tests: Halstead–Reitan finger tapping, simple reaction time test, and Beery Visuomotor Integration test. Impairments were identified as test scores of participants with TBI that fell outside of the 95% interval of control participants’ test scores. Random forest analysis was used to calculate the sensitivity and specificity of MMC and clinical tests according to their ability to correctly classify participants with TBI and control participants. Results: MMC-mediated tests revealed impairments in more participants with TBI than clinical tests in all three TBI groups (mild, repeated, and moderate to severe). Similarly, MMC-mediated tests revealed a higher percentage of scores as impairments than clinical tests in all three groups with TBI. Furthermore, MMC-mediated tests proved more sensitive and more specific than clinical tests (70% versus 50% and 98% versus 93%, respectively). Conclusion: MMC-mediated tests are sensitive and specific (compared to traditional clinical tests) and have potential to fill a gap in clinical care of TBI.

Survey: A Study On Image Encryption Using Dna In Bioinformatics, Rana M. Zaki, Zaed S. Mahdi, Matheel E. Abdulmunim

Journal of Soft Computing and Computer Applications

One area of study between computer science and biology is bioinformatics, which deals with methods for collecting, processing, storing, and evaluating biological data. Sequences of RiboNucleic Acid (RNA), DeoxyriboNucleic Acid (DNA), and proteins make up biological data, which has a wide range of uses in domains such as feature extraction, data segmentation, data security, and more. In cryptography, DNA sequences are used as data carriers, enhancing the unique properties of biomolecules. This approach involves using DNA sequences to enhance the security of confidential data that must be transmitted over networks or stored securely. Several DNA-based security techniques have been developed, …

Enhancing Image Classification Using A Convolutional Neural Network Model, Zena M. Saadi, Ahmed T. Sadiq, Omar Z. Akif, Marwa M. Eid

Journal of Soft Computing and Computer Applications

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as …

2024 Scholarly Productivity Report, Missouri University Of Science And Technology

Civil, Architectural and Environmental Engineering Scholarly Productivity Reports

No abstract provided.

Decomposition Of Diisopropyl Methylphosphonate (Dimp) Exposed To Elevated Temperatures And Combustion Products Of Reactive Materials, Elif Irem Senyurt

Dissertations

The safe and efficient destruction of chemical weapon agents (CWAs) stockpiles remains a critical global challenge. Understanding the thermophysical properties, decomposition mechanisms, and interactions of CWAs with their environment is crucial for developing effective strategies to mitigate their threats. Diisopropyl methylphosphonate (DIMP) and Dimethyl methylphosphonate are commonly used nerve agent surrogates. This dissertation focuses on DIMP and DMMP, investigates their properties and behavior under conditions relevant to prompt defeat scenarios.

The thermophysical properties of DIMP and DMMP were experimentally characterized, including vapor-liquid surface tension (3-60 °C) and viscosities of neat and aqueous solutions. Results revealed significant non-ideal behavior in aqueous …

Optimizing Bioethanol Production From Solanum Torvum (Devil's Thorn): An Evaluation Of Conversion Efficiency And Invasive Plant Management Potential, Jaya Ashwin D S, Navaneeth K, Abhay Mahesh Baadkar, Supriya S Sundar, Bhoomika B J

Manipal Journal of Science and Technology

Solanum torvum, commonly known as the Devil’s thorn, is an invasive species present in India that causes negative ecological consequences. However, given its abundance and high starch content in the plant, it could be utilized as a potential feedstock for sustainable biofuel production. We aim to explore the feasibility of bioethanol production from S. torvum and its potential as a means of managing this invasive species. The study will take on a comprehensive approach, including techniques for optimizing starch extraction and improving its accessibility. Fermentation with suitable strains of microorganisms, and analysis of bioethanol yield. In addition, the study will …

An Energy-Efficient Clustering Technique Of Heterogeneous And Homogeneous Wireless Sensor Networks, Ahmad Alkhayyat, Rohit Sharma

NJF Intelligent Engineering Journal

The technology of wireless sensor networks (WSN) has recently gained widespread recognition as an emerging one. A WSN consists of a set of sensors powered by batteries. Inaccessible locations usually make it difficult to replace or recharge sensors' batteries. These networks are plagued by energy consumption, which is the main problem. The clustering algorithms are remarkably effective in dealing with such problems in this regard. As a result, this technique appears to help reduce node energy consumption, which ultimately increases the network's lifespan. Heterogeneous and homogeneous clustering algorithms exist. In homogeneous clustering algorithms, all nodes have the same technical characteristics, …

Optimized Thyroid Disease Classification Using Nature-Inspired Algorithms: Gwo & Woa, Sayan Mondal

NJF Intelligent Engineering Journal

Recently, there has been an upsurge in the number of cases of thyroid disease. Thyroid function is essential for metabolism, making the early diagnosis of thyroid dysfunction an urgent matter. The issue of class imbalance has not been thoroughly examined, even though there are multiple publications on the topic of thyroid disease detection. Furthermore, the binary-class problem has been the primary emphasis of previous research. This study intends to address these concerns by using the suggested strategy, which takes into account ten distinct thyroid illnesses. In order to choose the best features from the Thyroid dataset, this research proposes two …

A Predictive Iot And Cloud Framework For Smart Healthcare Monitoring Using Integrated Deep Learning Model, Preeti Rani, Umesh Chandra Garjola, Haider Abbas

NJF Intelligent Engineering Journal

The researchers developed a deep learning-based smart healthcare monitoring system based on IoT and cloud technology. The proposed system integrates IoT sensors for real-time collection of physiological data, such as ECG, blood pressure, and heart rate, with cloud computing for secure storage and advanced analytics. Utilizing the Bi-LSTM model with fuzzy inference systems (FIS), the framework enhances the accuracy and efficiency of heart disease prediction. According to the evaluation, the model performs better in terms of accuracy, precision, recall, and F1 score than traditional LSTM and FLSTM models. By enabling early detection and personalized interventions, the system aims to reduce …

A Predictive Framework Combining Iot And Machine Learning Regression Models For Smart Precision Farming, Kusum Yadav, Nesreen Abdou El-Hadiede

NJF Intelligent Engineering Journal

In this paper, the Internet of Things (IoT) and machine learning algorithms that incorporate regressor are integrated to improve precision agriculture. Data from Internet of Things sensors like temperature sensors, humidity sensors, and soil sensors can be collected and analysed using machine learning algorithms like Support Vector Machines (SVMs) and Multilayer Perceptrons (MLPs). By using the proposed system, crop yield will be optimised, resource usage will be minimised, and the environmental impact of agriculture will be reduced. A comparison of predictive accuracy and error metrics, such as RMSE, demonstrated the effectiveness of automated monitoring, predicting crop health issues, and implementing …

Comparative Analysis Of Nature-Inspired Optimization Algorithms: Applications, Challenges And Future Directions, Prerna Mann

NJF Intelligent Engineering Journal

With the proliferation of data generation, the process of achieving optimal solutions is getting more complex. It is becoming increasingly clear that intelligent metaheuristics algorithms are the way to go for solving these complicated optimisation problems, particularly when faced with several restrictions. The development of effective methods for dealing with these optimisation challenges has prompted the creation of numerous new algorithms. These algorithms are either improving their ability to handle problems in many domains or are investigating new contexts in which they could be useful. The field is advancing at a quick pace, leaving many in the dark about its …

Developing A Roadmap For Green Port In Timor-Leste, Emanuel Da Silva Maia

World Maritime University Dissertations

No abstract provided.

Green Design Of Plant Based Pharmaceutical Drugs: Example Of A Wound Healing Topical Cream With Plectranthus Bojeri (Benth) Hedge Lamiaceae Extract, Helga Rim Farasoa, Marie Louise Razafindravao, Rojo Fanambinantsoa Andriamiarantsoa, Gerard Cecilien Raboanary, Jean Marie Razafindrakoto, Voahangy Ramanandraibe Vestalys

Journal of Bioresource Management

To ensure the perennity of natural resources, the valorisation process of herbal pharmaceuticals must be assessed for sustainability from the very beginning of its design. No specific tools have been developed for this particular field so far. We demonstrate in this study that existing green design tools can be adapted to evaluate plant-based products manufacturing process. As the example of a topical cream using Plectranthus bojeri (Benth) Hedge LAMIACEAE extract was considered, we first confirmed the traditional use of this plant for wound healing. It acts by accelerating the re-epithelialisation phase. Using the Vermeer Cosmolife version 0.24 software tool the …

Forecasting Air Pollution Driven By Vehicle Growth, Public Transport, Industry, And Household Waste, Chandra Harjono, Ludy Gianto, Rachmattullah Sidik, Dyah Lestari Widaningrum

Journal of Environmental Science and Sustainable Development

Jakarta, Indonesia's bustling capital, is grappling with escalating air pollution levels attributed to a confluence of socio-economic and infrastructural factors. This study employs Vensim modelling to project PM2.5 pollution trends through 2040, analysing the dynamic interplay among major contributors: increased vehicular emissions, industrial activities, public transportation deficiencies, and waste management inefficiencies. Materials and Methods: The method that will be used in this air pollution analysis is to integrate empirical data spanning three years to construct a predictive model underpinned by a robust causal loop diagram that elucidates the relationships between system variables and air quality. The results of this paper …

Assessing The Environmental Impact Of Municipal Solid Waste, Ojo Oluwayinka Florence, Olaniyan Olatunji Sunday, Akolade Adebola Saheed, Alabi Oluwaseyi Omotayo, Olaomotito Precious Adesope, Adebayo Kehinde John

Journal of Environmental Science and Sustainable Development

Municipal solid waste (MSW) management presents significant environmental challenges, especially with increasing urbanization and population growth. This study assesses the environmental impacts of MSW, focusing on waste composition, management practices, and their effects on air, water, and soil quality. The primary objective is to evaluate how MSW contributes to environmental degradation and to explore strategies for mitigating these impacts. A hypothesis was developed that optimizing waste composition through proper sorting and treatment can reduce the environmental footprint of MSW management by at least 10% in terms of leachate production and greenhouse gas emissions. Samples were collected using a randomized sampling …

Cropsync: Ai-Powered Sustainable Crop Management, Ziad Doughan, Ibrahim Mneimneh, Zouheir Nakouzi, Noor Al Khaib, Samer Damaj, Jamal Chaaban, Hamza Mrad, Sari Itani

BAU Journal - Science and Technology

CropSync is a smart agriculture system that uses AI and IoT technologies to enable sustain- able crop management and precision farming. The system aims to address the challenges faced by the agriculture sector, such as increasing food production to meet global population demands while minimizing environmental impact. CropSync integrates sensors, cameras, and cloud-based analytics to provide farmers with real-time insights and recommendations for optimizing crop cul- tivation. The system upholds engineering professional and ethical standards, considering broader social, environmental, and economic implications. From a social perspective, CropSync improves food security and enhances farmers’ livelihoods through increased productivity and efficient re- …

Energy-Efficient Technologies For Drying Mulberry Silkworm Cocoons Using Infrared Radiation, Doston Ishmukhammat Ugli Samandarov

Technical science and innovation

The article presents the results of theoretical and experimental studies on drying of mulberry silkworm cocoons. Based on the analysis of drying efficiency and silk quality, the use of infrared radiation (IR) at a temperature of 70 °C was found to be optimal. The experimental data were tested on six mathematical models, among which the Midilli model most accurately described the drying process. The effective moisture diffusion coefficient was found to vary in the range of 1.847×10^-⁹-4.339×10^-⁹ m²/s, and the drying rate was found to be 0.32-0.79 kg of water/hour. IR radiation promotes accelerated evaporation of …

Energy Saving Technology For Drying Garlic (Allium Sativum), Jasur Esirgapovich Safarov, Shakhnoza Abduvaxitovna Sultanova, А M. Mirkomilov

Technical science and innovation

Food drying is a widely used preservation method aimed at reducing water content to extend shelf life, decrease weight, and enhance storage efficiency. This process, particularly in garlic, involves rapid initial moisture loss followed by a slower phase due to the increasing difficulty of extracting residual water. Drying methods include natural solar drying and advanced mechanical techniques such as hot air and vacuum drying, each influencing product quality, drying efficiency, and economic feasibility. Dehydrated garlic exhibits specific sensory, physico-chemical, and microbiological characteristics, making it suitable for various applications, including powder production. Advanced drying equipment optimizes air volume, temperature, and material …