Digital Commons Network^™

Biosynthesis Of Metallic Nanoparticles Using Plant Extracts: Mechanisms, Advances, And Sustainable Applications, Alice Njolke Mafe, Great Iruoghene Edo, Patrick Othuke Akpoghelie, Endurance Fegor Isoje, Ufuoma Augustina Igbuku, Joseph Oghenewogaga Owheruo, Arthur Efeoghene Athan Essaghah

Al-Mustaqbal Journal of Sustainability in Engineering Sciences

Growing concerns over the environmental and health impacts of conventional nanoparticle synthesis have driven a shift toward green, plant-based methods. This review highlights the biosynthesis of nanoparticles using plant extracts as a sustainable, economical and non-toxic alternative. Plant-derived phytochemicals such as flavonoids, phenolics, and alkaloids serve dual roles as natural reducing and stabilizing agents, enabling the production of nanoparticles typically ranging between 10 and 100 nm. Several studies have demonstrated up to 80% yield improvement when using optimized extracts from plants like Azadirachta indica and Ocimum sanctum. The review outlines recent progress, including the use of novel botanical sources, …

Comparative Analysis Of Gas And Mechanical Emissions From Electric Cars And Internal Combustion Engine Vehicles, Bakhtiyor Akhmatjonovich Kosimov

Technical science and innovation

This article analyzes the environmental impact of modern cars, in particular the amount of harmful substances emitted into the environment by electric cars and internal combustion engine cars, and provides scientific information on the substances that are released from cars in the form of not only gaseous emissions, but also dust particles generated by the mechanical wear of the brake system and tires. At the same time, this article also takes a scientific approach to the wear rates of brake pads and tires, their impact on environmental safety, and the level of dispersion of the microdust generated. Comparative tables have …

Harnessing Environmentally Healthy Approaches For Plastic Degradation: A Review And Future Perspectives, Marc Chojnacki

Beyond: Undergraduate Research Journal

In the face of escalating plastic pollution, innovative degradation strategies, such as enzymatic degradation, smokeless incineration technology, and biodegradable plastics, are gaining traction. This paper collates comprehensive research on these methods, assessing their environmental impact and operational feasibility. A special focus is placed on the role of technology and its capacity to spark advancements in these degradation strategies as well as to draw on specific research to understand the economic implications of these methods. At the core of this study is the exploration of potential new, inventive degradation methodologies. Through examining methods of green plastic degradation, the study aims to …

Investigating Vacuum Insulator Flashover Resistance Of Rexolite And Acrylic Before And After Applying Novel Insulator Cleaning Techniques, Ritin Joseph

Electrical and Computer Engineering ETDs

Pulsed power involves accumulating large amounts of electrical energy and releasing it instantaneously. Large pulsed power accelerators use a vacuum insulator stack to facilitate power transfer from the liquid to vacuum section. Limiting the probability of surface flashover in this setting to acceptable levels improves machine longevity and prevents energy loss. Post-shot debris deposition requires a refurbishment process to prevent deterioration of dielectric performance, though the current technique of hand-sanding is long, labor-intensive, and pose serious health hazards. I have collected flashover data on frustrum-shaped Acrylic and C-Lec Rexolite® (cross-linked polystyrene) samples using a 500-kV, 20-ns risetime pulsed power test …

Enhanced Detection Of Intracranial Hemorrhage: A New Hybrid Model Design Based On The U-Net Segmentation Method, Hassan F. Hassan, Hadeel K. Aljobouri, Oktay Algin

Iraqi Journal for Computer Science and Mathematics

Intracranial hemorrhage (ICH) denotes bleeding inside the skull, which can occur in or around the brain. Computed tomography (CT) has been used to detect ICH due to its high efficiency and accuracy. Nowadays, deep learning model design is introduced to allow an accurate and efficient classification of ICH in CT images. This work focused on developing U-Net-based models for the segmenting of ICH. Furthermore, the proposed model employed two transfer learning models, MobileNet and Xception, as the backbones of the U-Net topology. This approach aims to establish metrics that improve ICH treatment through precise segmentation techniques. A free dataset from …

Retracted: A Novel Benchmarking Framework For Selecting The Best Deep Learning Model Diagnosing Covid-19 Based On New Development For Dual Mcdm Methods, Mahmood M. Salih, Yousif Raad Muhsen, M.A. Ahmed, Reem D. Ismael, Moceheb Lazam Shuwandy, Z.T. Al-Qaysi

Iraqi Journal for Computer Science and Mathematics

COVID-19 was diagnosed using deep learning models by a group of studies. Evaluating and benchmarking these models are essential to achieving the most suitable model for diagnosing coronavirus. Objective: In this investigation, we offer an inclusive valuation of several deep learning models to detect the maximum appropriate and active model which gratifies doctors' requirements and assessment criteria. Method: This study combines Fuzzy decision by the opinion score method (FDOSM) and Fuzzy-Weighted Zero-Inconsistency (FWZIC). According to the advantage of Trapezoidal Intuitionistic fuzzy, we developed FWZIC into Trapezoidal Intuitionistic fuzzy named (TrIF-FWZIC) for weighting criteria and FDOSM into Trapezoidal Intuitionistic fuzzy FDOSM …

Leveraging Machine Learning For Accurate Prediction Of Nba Player Salaries, Ye Cheng, Yan Song, Mingqi Wang

Iraqi Journal for Computer Science and Mathematics

Basketball players in the NBA are renowned for their talent, athleticism, and commitment to the game. NBA players may make enormous sums of money; however, they vary greatly. Rookie agreements begin at a lower price and go up following performance. NBA players’ pays are influenced by several factors. Because they influence games and the success of the club, exceptional players fetch larger compensation. This study employs Machine Learning (ML) techniques, including Lasso Regression and Random Forest Regression (RFR) models to analyze wage trends, enhanced by the Slime Mould Algorithm (SMA) and Artificial Rabbit Optimization (ARO) for accuracy. The goal is …

Green Energy Production Using A Hydro-Generator In An Underground Mine Water Pumping Station – Case Study, Andrzej Chmiela, Beata Barszczowska, Eugeniusz Krause, Arkadiusz Kulawik, Adam Smolinski

Journal of Sustainable Mining

The paper analyses the experience of almost one year of production of “green” electricity by a hydro-generator using a constant water drop in the pits of mine water pumping stations. The main technical, economic and environmental parameters obtained by the applied technical and organisational system are presented. Equipping the mine water pumping station with a hydro-generator proved to be a good investment. The investment offers a relatively low risk with a relatively low initial outlay and a relatively short payback period of about 4 years. The innovative use of typical but modern elements in an atypical operating environment has not …

Assessing The Living Conditions Of Mining-Induced Resettled Persons: The Case Of Ahafo South Resettlement Communities, Ghana, Jonathan Zinzi Ayitey, Mustapha Okyere, Frank Gyamfi-Yeboah

Journal of Sustainable Mining

This study examines the living conditions of mining-affected persons in the Ahafo South Mining Communities in Ghana using Cernea’s Impoverishment Risks and Reconstruction (IRR) model. Employing a case study design, data for the study was obtained through a combination of semi-structured interviews and close-ended questionnaires administered to ninety (90) respondents in the Ntotroso and OLA resettlement communities in the Asutifi North District, Ghana. The results show a complex mix of outcomes of mining-induced displacement and resettlement of the resettled population. While an analysis of resettlement impacts found a high level of satisfaction among the resettled population with housing provision, road …

Exploring The Interactions Between Mining And Climate Change: A Bibliometric Analysis, Artatrana Mishra, Sarat Chandra Sahu, Manish Yadav, Nitin Kumar Singh

Journal of Sustainable Mining

The increasing demand for minerals has placed huge pressure on the mining industry to increase production, which consequently affects the environment, and, thus, contributes to climate change. Coal extraction has been reported to be a major contributor to global CO₂ emissions, mainly due to the burning of fossil fuels. As a consequence, the frequency and severity of extreme climatic events have also increased throughout the world. Mining is essential for the development of society but contributes to climate change. On the contrary, extreme weather events and rising temperatures associated with climate change affect the overall productivity of mining companies. …

Evaluation Of Cyanide Removal Processes On Water Effluents From Gold Ore Processing And Industrial Scale Up, Juliana Freitas, Jorge Bellido

Journal of Sustainable Mining

Gold extraction goes through different steps, from research to physical-chemical processing, which uses chemical reagents for extraction, such as cyanide. In literature, there are presented many ways to remove cyanide from this effluent on a bench scale, although on an industry scale it is not very often analysed. In this study, seeking innovation on an industrial scale for cyanide removal from real effluent generated by gold processing was analysed through oxidation with H₂O₂ and Fenton process. It was proven that these processes can remove cyanide at the levels required for recirculation of the effluent in the process, …

Cognitive Diversity, The Keystone To Effective Ptd In The Medical Research And Medical Device Industries, John Gilmartin

ASEM Capstones

2025 ASEM 620 Capstone Project

Understanding Risk For Industrial Emergency Response Teams, Terill A. St Martin

ASEM Capstones

2025 ASEM 620 Capstone Project

Application Of Polymer Nanocomposites In The Design Of Prosthetic Sockets That Feature Auxetic Meta-Structures, Sumit Suryakant Kolte, Vinayak Vijayan, Lihua Lou

Publications

This research evaluates the response of prosthetic sockets constructed using polymer nanocomposites and incorporating auxetic meta-structures. The prosthetic sockets feature lightweight meta-structures between the inner and outer walls of the socket. Three different prosthetic designs featuring chiral, reentrant hexagon, and honeycomb meta-structures are evaluated in this study. The prosthetic sockets were designed in SolidWorks and compared using finite element analysis. The polymer nanocomposites used in this study include polypropylene and ultra-high molecular weight polyethylene containing uniformly distributed inclusions of either titanium dioxide, zinc oxide, or graphene nanoplatelets. Our results show a favorable pressure profile at the interface between the prosthetic …

Geophysical Tools For Agricultural Management: Trends, Challenges, And Opportunities, Sophia Becker, Trenton Franz, Yufeng Ge, Joe Luck, Derek M. Heeren

School of Natural Resources: Faculty Publications

Agrogeophysics is a convergence of proximal soil sensing and hydrogeophysics in which geophysical methods are used to describe soil patterns and dynamics that shape agronomic management (including precision agriculture). To fully realize its potential for optimizing agricultural production, current barriers and targets for future agrogeophysics research must be identified. In this review, we compare the trajectory of agrogeophysics within peer-reviewed literature, patents, and the US university extension literature and examine the current challenges and opportunities for supporting agricultural production and sustainability with agrogeophysical tools. We conducted a repeatable search of Web of Science and Scopus for seven geophysical methods (electromagnetic …

Geopolymer Clsm With Off-Specification Fly Ash And Bottom Ash: A Sustainable Approach To Hazardous Waste Utilization, Alexis K. Vandomelen, Ahmed A. Gheni, Eslam Gomaa, Mohamed A. Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Conventional controlled low-strength material (CLSM) is a self-consolidating cementitious material with high flowability and low strength, traditionally composed of cement, sand, and water. This study explores the sustainable utilization of off-specification fly ash (OSFA) and bottom ash (BA), classified as industrial by-products with potential environmental hazards, to develop eco-friendly geopolymer CLSM as an alternative to conventional CLSM. Sodium hydroxide (NaOH) was used as an alkali activator to stabilize and solidify both two-part (liquid NaOH) and one-part (solid NaOH pellets) geopolymer CLSM mixtures. These mixtures were evaluated based on flowability (ASTM D6103-17) and compressive strength (< 300 psi per ACI Committee 229 guidelines for excavatability). A cost analysis was also conducted. The results demonstrated that incorporating OSFA as a cement replacement increased water demand by 15% to meet flowability requirements, while BA substitution for sand led to segregation challenges requiring mixture adjustments. For two-part mixtures, higher carbon content in OSFA necessitated an increased water-to-fly ash ratio. All self-consolidating mixtures exhibited 1-day compressive strengths ranging from 5 psi (0.03 MPa) to 87 psi (0.6 MPa). One-part mixtures showed a 1% to 34% reduction in 7-day compressive strength compared to two-part mixtures, improving excavatability. Increasing the BA-to-OSFA ratio from 1:1 to 3:1 reduced water demand due to lower surface area but increased the NaOH/OSFA ratio. This study highlights the potential of geopolymer CLSM to reduce costs by up to 94% at current NaOH prices (USD 6 per cubic yard) while repurposing hazardous industrial by-products, offering a cost-efficient, sustainable, and environmentally responsible solution for CLSM production.

Aeolus-Ds: Dust-Aware Ai Decision Support For Coccidioidomycosis (Valley Fever) — A Design Science Research Framework Integrating Aerosol Remote Sensing, Land Disturbance, And Clinical Sentinel Signals, Harsha Sammangi, Aditya Jagatha, Harshini Balaga

Research & Publications

This paper presents Aeolus-DS, a design science research (DSR) artifact that integrates aerosol remote sensing (MAIAC AOD; dust fraction), mesoscale meteorology and soil moisture (ERA5), land-disturbance telemetry (construction, off-road vehicle activity, nightlights) and clinical sentinel signals (syndromic ED chief complaints, pneumonia rule-out) into a dust-aware, AI-driven early warning and decision-support system for Coccidioidomycosis (Valley Fever). Methodologically, we propose a graph spatiotemporal transformer with direction-aware attention and physics-guided regularisation reflecting aeolian transport. Using county-week panels (2014-2024) for the U.S. Southwest (AZ–CA–NV), Aeolus-DS improves now-casting mean absolute error (MAE) by 18% and two-week area under precision-recall curve (AUPRC) by 21% over …

Building Social Butterflies And Learning Circles: The Key To Organizational Safety Potential, Trevor Farr

ASEM Capstones

2025 ASEM 620 Capstone Project

Creating Blood Analogs To Mimic Steady-State Non-Newtonian Shear-Thinning Characteristics Under Various Thermal Conditions, Hang Yi, Alexander Wang, Christopher Wang, Jared Chong, Chungyiu Ma, Luke Bramlage, Bryan Ludwig, Zifeng Yang

Mechanical and Materials Engineering Faculty Publications

Blood analogs are widely employed in in vitro experiments such as particle image velocity (PIV) to secure hemodynamics, assisting pathophysiological diagnoses of neurovascular and cardiovascular diseases, as well as pre-surgical planning and intraoperative orientation. To obtain accurate physical parameters, which are critical for diagnosis and treatment, blood analogs should exhibit realistic non-Newtonian shear-thinning features. In this study, two types of blood analogs working under room temperature (293.15 K) were created to mimic the steady-state shear-thinning features of blood over a temperature range of 295 to 312 K and a shear range of 1~250 s−1 at a hematocrit of ~40%. Type …

Sidesense: Robust Physiological Motion Detection Via Mmwave Joint Communication And Sensing Systems With Multiple Beams, Mohammed Shadman Ishrak, Jannatun Noor Sameera, Alvin Yang, Yanjun Pan, Yao Zheng, Olga Boric-Lubecke, Victor M. Lubecke

Electrical Engineering and Computer Science Faculty Publications and Presentations

A 28-GHz multibeam joint communication and sensing system called SideSense is presented, in which a line-of-sight (LoS) beam is used to maintain reliable communication, while other sensing beams are used to enhance physiological motion detection. SideSense decodes the motion frequency and shape from the channel state information (CSI) by first tuning the gain ratio and phase differences between the LoS communication beam and non-LoS (NLoS) beam to maximize the sensing signal-to-noise ratio (SSNR) without significantly degrading the communication channel capacity (CCC). Analytical results based on a bistatic model are presented to show a gain ratio of around 1 and a …

Differential Privacy Enabled Deep Skin Image Classification Model Development, Prasun Kumar Mandal

Master’s Dissertations

Abstract In the era of big data, the explosive growth in data volume has significantly accelerated the development of deep learning. Deep learning is the most promising area of AI, yielding significant advancements in medical image classification. However, healthcare data contains important sensitive information and so privacy and security are crucial to preventing unauthorized access. Note that there are several data protection rules from multiple regulations to penalize any kind of data security violation, for example, the data protection principles (Article 5.1-2) and the data protection by design and by default (Article 25) of the General Data Protection Regulation from …

Gallium-Containing Bioactive Glasses: Their Influence On Ion Release And The Bioactivity Of Resulting Glass Polyalkenoate Cements, Lana Margaret Placek, Danielle Lee Perry, Mark Robert Towler, Anthony William Wren

Chemical and Biochemical Engineering Faculty Research & Creative Works

A series of glasses (0.48SiO2 − [0.40-x]ZnO − 0.12CaO-xGa2O3, x = 0, 0.8, 0.16) was developed to formulate a series of Ga-containing glass polyalkenoate cements (GPCs). The solubility of GPCs was tested using DI water, and it was found that the sample containing the highest mol% of Ga, LGa-2, had the most Ga ion release. The GPCs were incubated in SBF, and SEM/EDS analysis revealed that the at% of P increased, while the at% of Si decreased, highlighting the CaP precipitation on the GPC surface. The at% of Ga also decreased, reinforcing the Ga release from the GPC. Cellular testing …

Enhanced Pavement Project Prioritization, Bryan Gibson, Jon Wilcoxson, Gayle Marks

Kentucky Transportation Center Research Report

The Kentucky Transportation Cabinet (KYTC) is responsible for inspecting, maintaining, and improving 27,000 centerline miles of pavement. Given the vastness of the state’s transportation network, KYTC needs a robust method for prioritizing pavement preservation projects. The Cabinet has relied on pavement condition ratings, data collected using Laser Crack Measurement Systems, and input from district-level staff to prioritize these types of projects. But this approach overlooks information that should be considered, such as factors related to safety, mobility, and geographic context. To resolve these shortcomings, Kentucky Transportation Center (KTC) researchers worked with KYTC subject-matter experts to develop the Enhanced Pavement Prioritization …

Data-Driven Prediction Of Binder Rheological Performance In Rap/Ras-Containing Asphalt Mixtures, Eslam Deef-Allah, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Asphalt recycling technologies have advanced considerably over the last few decades with the utilization of reclaimed asphalt pavements (RAP) and recycled asphalt shingles (RAS). Characterizing aged and heterogeneous binders in these mixtures is challenging, particularly with limited extracted binders. This study suggests a data-driven framework that considers the rheological, chemical, and thermal characteristics to predict the binders' performance. Ninety-seven mixtures with 0–35% of the asphalt binder replaced with RAP/RAS binders were included as cores from the field, plant-produced mixtures, and laboratory-fabricated mixtures. The binders were chemically quantified using aging, aromatic, and aliphatic indices. Thermal analyses of the binders involved the …

Towards Accountability: A Primer On The Space Debris Problem And An Overview Of The Legal Issues Surrounding It, William Schonberg

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Since 1957, the near-Earth population of trackable space objects has grown in number to over 36,000. Of these 36,000+ trackable objects now in low Earth orbit, just a few thousand are working spacecraft. The rest are Earth-orbiting objects which are no longer operational and are considered to be space junk. Because this junk can no longer receive maneuvering commands from its Earth-based owners, the survivability of other spacecraft traveling through or operating in Earth orbit can be jeopardized by the impacts of any number of pieces of this space junk, whose origins can usually be traced back to defunct satellites. …

Data-Driven Methods For Signal Analysis And Nonlinear System Identification, Cristian Felipe López Ruano

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

In recent years, data-driven modeling has gained considerable attention in nonlinear system identification, offering a powerful alternative to traditional physics-based methods. This has been possible by advances in machine learning, sparse regression, and differential equations in a weak form, which allow the accurate capture of complex nonlinear dynamics, even when the measurements are in strong background noise. Moreover, integrating these models with physical knowledge further enhances their reliability and interpretability, making them suitable for a wide range of science and engineering applications.

In this dissertation, we investigate algorithms for data-driven nonlinear system identification to obtain ordinary differential equations that govern …

Development And Implementation Of A Vector-Quantized Transformer Autoencoder For Monitoring Bicycle Road Conditions, Kewei Ren

Department of Construction Engineering and Management: Dissertations, Theses, and Student Research

Adviser: Chun-Hsing Ho

The long-term, sustainable assessment of bicycle road conditions is essential for ensuring cyclist safety and promoting equitable infrastructure management. While traditional detection methods based on manual thresholds have demonstrated some effectiveness, they carry limitations due to the diversity of pavement materials, cyclist behaviors, and sensor platforms. Although recent advances in deep learning offer promising alternatives, established techniques are primarily applied to highway anomaly detection and are rarely adapted for bicycle roads. Furthermore, most related studies lack clear definitions for anomalies and transparent annotation procedures, resulting in a shortage of effective datasets and detection methods specifically for bicycle …

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Ziad Khalifa, Kyrillos Selim, Amira Ali, Sameh Abdellatif

Chemical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)- based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a …

Investing Hysteresis In Floodplain Dynamics Of Lakes In The Middle St. Johns River Using Sentinel-1 Sar Imagery, Keenan Hubbard

Doctoral Dissertations and Master's Theses

Floodplain dynamics are often complex, with hysteresis potentially affecting the temporal relationship between flood stage and flood extent during subsequent inundation phases. This study leverages Sentinel-1 synthetic aperture radar (SAR) imagery to map flood extent in the Middle St. Johns River Lake floodplains and examine the presence of hysteresis during flood events. SAR scenes corresponding to river gauge readings were analyzed from the rising and falling limbs of a flood hydrograph. By comparing these flood maps, we assess differences in inundated areas at equivalent water levels during each stage of the flood event. The findings aim to enhance flood monitoring …

Experimental Analysis Of Satellite Operator Training Using Game-Based Virtual Reality Simulation, Lana Laskey

Doctoral Dissertations and Master's Theses

Satellite data plays a vital role in modern global infrastructure by enabling communications, navigation, and weather forecasting. As demand for satellite technology grows, so does the need for highly trained satellite ground operators. Traditional training regimens for satellite operators employ simulation using two-dimensional computer console displays paired with the varied ability of trainees to generate abstract mental imagery of the scenario. However, this development of mental imagery imposes a considerable learning curve and cognitive workload on the trainee, which may negatively impact the user experience and knowledge gained during the training scenario.

This experimental study investigated the effects of game-based …