Digital Commons Network^™

A Nonenzymatic Electrochemical Glucose Sensor Depending On A Ninps/Co3o4/Functionalized Graphene Oxide-Modified Working Electrode, Sümeyra Pekmez, Muhammet Güler

Turkish Journal of Chemistry

In the present research, the aim was to develop a novel electrochemical enzyme-free glucose sensor dependent upon a nickel nanoparticles (NiNPs)/cobalt (II, III) oxide (Co3O4)/carboxylated graphene oxide (GO-COOH)-modified glassy carbon (GC) electrode. The electrocatalytic performance of the electrode was tested using various electrochemical methods such as amperometry and cyclic voltammetry (CV). The NiNPs@Co3O4/GO-COOH/GC electrode showed noticeably superior electrocatalytic behavior for glucose oxidation in 0.1 M NaOH media, ascribed to the good synergistic impact between NiNPs, Co3O4, and GO-COOH. The amperometric response of the NiNPs@Co3O4/GO-COOH/GC electrode to glucose exhibited two linear determination ranges at +0.55 V potential. The first one was …

Synthesis Of Two Hofmann-Type-Like Clathrates, Characterizations, And Investigation Of Their Structures, Spectroscopic And Theoretical Properties, Zari̇fe Si̇bel Şahi̇n, Zeki̇ Kartal

Turkish Journal of Chemistry

This study concerns two Hofmann-type-like clathrates using 4-aminopyridine (4AP) as ligands and the transition metal atoms copper (Cu) and zinc (Zn). These clathrates have the structural features of heteronuclear tetracyanonickelate(II) and contain H2O and 4AP molecules as guest molecules, respectively. These two clathrates were characterized by infrared spectroscopy (IR), elemental analysis, and single crystal X-ray diffraction (SC-XRD) techniques. Based on elemental and spectral data, the structural formulae describing these clathrates were found to be [Cu(II)(4AP)4Ni(μ-CN)2(CN)2]·H2O (1) and [Zn(II)(4AP)4Ni(μ-CN)2(CN)2]·(4AP) (2). In addition, the values of some optical, electronic, and thermochemical properties of the two obtained clathrates calculated with the Gaussian 03 …

A Modular Saponin Adjuvant Platform: Development, Structure–Activity Relationships, And Applications, Di Bai

ETDs from 2020-2029

ABSTRACT Saponin-based vaccine adjuvants have attracted considerable attention owing to the clinical success of QS-21, a potent immunostimulant capable of inducing balanced humoral and cellular immune responses, yet its widespread application is limited by supply constraints, chemical instability, and dose-dependent toxicity. To address these challenges, we previously developed two semisynthetic saponin adjuvants, VSA-1 and VSA-2, derived from abundant Momordica saponins through a single-step modification, which exhibit QS-21–comparable immunopotentiating activity with improved accessibility and stability. Here, we first performed a systematic structure–activity relationship (SAR) study of the VSA series using MS I as the lead scaffold. Modulation of the side-chain length …

Investigation Of Air Emissions With A Local Composites Industry, Chris White

ETDs from 2020-2029

Workers at an office space raised complaints about a sweet-smelling odor directly outside their building. After an initial assessment of the surrounding businesses and their processes, it was determined that the workers were most likely exposed to styrene emissions from a nearby composites company. This investigation utilizes multiple weeks of direct readings with a photoionization device and active environmental sampling with a charcoal tube and pump to confirm the styrene exposure hypothesis. Weather trends were also recorded to determine correlation between weather and exposure to the sweet-smelling chemical. The direct readings found an exposure maximum of less than 2 ppm …

Efficient Heterogeneous Photo-Fenton Degradation Of Azo Dyes Using The Nanocomposite Mgfe2o4/Mos2, Zahra Zeinali, Leila Ershadi Afshar, Naz Chaibakhsh, Farnaz Isapour

Turkish Journal of Chemistry

In the present work, a facile hydrothermal route was employed to synthesize the nanocomposite MgFe2O4/MoS2, which acted as a heterogeneous photo-Fenton catalyst for the degradation of a synthetic diazo dye, Acid Blue 113 (AB113). The nanocatalyst produced underwent analysis using multiple characterization techniques. The parameters influencing the oxidative reaction were statistically modeled and optimized using response surface methodology. Optimal degradation efficiency for AB113 (94.92%) was attained at pH 8.79 using 10 mg of MgFe2O4/MoS2 nanocatalyst, 1.6 mL of H2O2, and a reaction duration of 27 min. The synergistic effect resulting from the formation of electron-hole pairs renders the combined photocatalysis …

Electrochemical Biosensing Of Alpha-Fetoprotein Based On Carboxylated Multi-Walled Nanotube-Polyazur A (In Des)-Gold Nanoparticles, Merve Yilmaz Çilçar, Meli̇ke Bi̇lgi̇ Kamaç

Turkish Journal of Chemistry

AFP, a cancer biomarker, is monitored during fetal development and in the serum of pregnant women. Sensitive and rapid monitoring of AFP is crucial for effective management. In this study, screen-printed carbon electrodes (SPCEs) modified with multi-walled carbon nanotubes (MWCNT-COOH), polyAzur A (PAA), which was prepared in a deep eutectic solution (DES), and gold nanoparticles (AuNP) were fabricated. AFP biosensors were developed for practical, sensitive, low-cost, and rapid detection of AFP. Optimizations of nanostructures (MWCNT-COOH, AuNP) and polymers (PAADES) were performed. The MWCNT-COOH, PAADES, and AuNP-modified SPCEs were characterized by FE-SEM-EDX, FTIR, and XRD techniques. The amounts of 6-MOH, APTES, …

Statistical Methods For Mendelian Randomization Under Nonlinearity And Non-Normality, Mary Appah

ETDs from 2020-2029

Instrumental variable (IV) methods are widely used for estimating causal effects in observational studies where unmeasured confounding may bias traditional regression estimates. The core idea is to use a variable referred to as an instrument that is associated with the exposure of interest, independent of unmeasured confounders, and influences the outcome only through the exposure. While originally developed in econometrics, IV methods have been increasingly adopted in epidemiology and genetic research under the framework of Mendelian Randomization (MR), where genetic variants, most commonly single nucleotide polymorphisms (SNPs), serve as instruments. MR provides a powerful tool for investigating causal relationships between …

Data-Driven Electrochemistry Reveals The Impact Of Hydrophobicity On Aptamer Cross-Reactivity, Emily Carroll, Michael A. Pence, Elizabeth Winterholler, Taylor D. Sparks, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Electrochemical aptamer-based (E-AB) biosensors offer a promising platform for reagentless detection of molecular targets, yet aptamer recognition can be limited by cross-reactivity, particularly for hydrophobic analytes such as steroid hormones. To investigate how cross-reactivity influences E-AB sensor performance, we use automation and machine learning to screen a library of possible interferent molecules against a steroid-binding aptamer, with progesterone serving as a physiologically relevant test case. Here, we develop a label-free E-AB sensor for progesterone detection using a methylene blue-modified aptamer anchored with a hexanethiol linker. We then used an automated electrochemistry platform to perform reproducible and high-throughput characterization of our …

High-Throughput Optical Analysis To Inform Design Of Electrochemical Biosensors, Nathan J. Ricks, Michael A. Pence, Monica Brachi, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Electrochemical biosensors are central to wearable diagnostics, point-of-care testing, and continuous health monitoring due to their low power requirements, compatibility with miniaturized electronics, and proven clinical impact. Despite these advantages, the development of new electrochemical biosensors remains slow, constrained by limited throughput, complex electrode–biomolecule interfaces, and challenges associated with selectivity and performance in chemically complex environments. This perspective outlines how the next generation of electrochemical biosensors can be enabled by decoupling high-throughput front-end discovery and optimization from electrochemical readouts using nonelectrochemical surrogate assays. Optical, affinity, and cell-sorting platforms, including SELEX, fluorescence-activated cell sorting, and chemically coupled fluorescence assays, allow orders-of-magnitude …

Student Worksheets Based On The Local Wisdom Of Besilek Serawai For Sixth-Grade Elementary Science Learning, Mice Agustin, Tomi Hidayat, Irwandi Irwandi

Jurnal Pendidikan Sains

This study aims to develop a Student Worksheet (Lembar Kerja Peserta Didik [LKPD]) based on the local wisdom of Besilek Serawai for sixth-grade elementary science education and to evaluate its validity. The study employed the ADDIE development model, consisting of five stages: Analyze, Design, Develop, Implement, and Evaluate. The developed LKPD integrates Besilek Serawai, a traditional martial art of the Seluma community, with the concept of the human locomotor system in science instruction. The worksheet was validated by two subject-matter experts and two media experts. Material validation yielded an average score of 4.26, equivalent to a validity percentage of 85.2%, …

The Effect Of Project-Based Learning Model On Entrepreneurship (Pjbl-E) With A Deep Learning Approach On Students' Problem-Solving And Cognitive Skills, Ricce Oktasari, Irwandi Irwandi, Siti Darwa Suryani

Jurnal Pendidikan Sains

This study aims to examine the effect of the Entrepreneurship-based Project Based Learning (PjBL-E) model integrated with a pedagogical Deep Learning approach on students’ problem-solving skills and cognitive learning outcomes in biology learning. The novelty of this study lies in the integration of entrepreneurship values and pedagogical deep learning principles into Project Based Learning to create contextual and meaningful learning experiences. Entrepreneurship integration encourages students to develop innovative products, identify real-world problems, and apply biological concepts in practical and socio-economic contexts. Meanwhile, the pedagogical Deep Learning approach promotes reflective thinking, conceptual understanding, critical analysis, and the ability to connect theory …

The Interplay Between Deficit Spending And Financial Instability: An Examination Of Fiscal And Monetary Policy Interactions, Heidie Jean George

Doctoral Dissertations and Projects

This study investigates the impact of fiscal and monetary policy on financial stability and fragility, focusing on how government spending and deficits contribute to the economic and financial system. Drawing on Minsky’s Financial Instability Hypothesis (FIH) and Financial Fragility Hypothesis (FFH), the research examines the dynamic relationship between fiscal policy, financial stability, and economic stability. The study focuses on understanding how government spending and deficits affect the economic and financial system in context of private and public debt and policy interactions and the role of system risk factors. The study uses Principal Component Analysis (PCA), Vector Autoregression (VAR), Impulse Response …

State Government, The Forgotten Cyber Actor, Joshua D. Strubel

Doctoral Dissertations and Projects

Cyber incidents are among the most pervasive threats facing the United States, with the FBI recording over 859,000 reported attacks and an estimated $16.6 billion in losses in 2024 alone. Despite widespread recognition that effective cyber defense requires a whole-nation approach, the existing research literature overwhelmingly focuses on federal policy, leaving state governments as largely overlooked actors. This study addresses that gap by examining the research question: How does state cybersecurity policy affect malicious cyber actors' frequency of operations? Drawing on multilinear regression analysis augmented by Random Forest machine learning models, this study evaluates the relationship between state-level cyber deterrence …

Adaptive Intervention Strategies In Co-Evolving Multiplex Networks: A Reinforcement Learning Approach To Real-Time Misinformation Containment, Anjali Ashokrao Bhadre Dr., Harshvardhan Prabhakar Ghongade Dr.

Northeast Journal of Complex Systems (NEJCS)

The growing transmission of misinformation via social media creates serious challenges to public health, democracy and social cohesion. To date, methods used to contain misinformation rely upon static representations of networks and set rules for interventions. In contrast, this study presents the first Multiplex Adaptive Reinforcement Intervention Network (MARIN), a framework for real-time adaptive intervention in the context of dynamic misinformation transmission using co-evolving multiplex networks and deep reinforcement learning. Unlike past studies that have assumed static network structures, MARIN has the ability to allow for dynamic changes in network topology as a result of both misinformation transmission and intervention …

Skin Lesion Classification Using Cnn Model And Augmented Dataset, Mohammed Nawzad Mohammed-Ramzi, Aso M. Aladdin

Journal of Soft Computing and Computer Applications

Skin cancer is a deadly disease. Skin lesion classification is a critical challenge due to its prevalent and deadly nature. Skin lesions are difficult for dermatologists to detect using eye examination, which is time-consuming and variable. A deep learning model of skin lesions classification has been proposed using a Convolutional Neural Network (CNN) trained on the HAM10000 dataset of 10,015 dermatoscopies. To improve resilience and address the dataset's extreme class imbalance, data augmentation techniques such as geometric transformations, brightness/contrast adjustments, blurring, noise addition, histogram equalization, color space alterations, and elastic deformations are used. With a carefully balanced 10% test set, …

Cardiovascular Disease Subtypes And Alzheimer's Disease: Phenotypic And Genetic Associations In The Uk Biobank And All Of Us Research Program, Aili Toyli, Chen Zhao, Kuan Jui Su, Hui Shen, Hong Wen Deng, Qing Hui Chen, Qiuying Sha, Weihua Zhou

Michigan Tech Publications

BACKGROUND: Cardiovascular disease (CVD) and Alzheimer's disease (AD) are major public health concerns that share overlapping risk factors and potential mechanistic pathways. Although vascular contributions to cognitive decline are well documented, the specific relationships between AD and different CVD subtypes remain poorly understood. METHODS: In this cross-sectional study, we examined associations between AD and 11 CVD subtypes using logistic regression models in 2 large biobanks: the UK Biobank (n=502 133) and the All of Us Research Program (n=287 011). Models were adjusted for demographic, lifestyle, and clinical covariates. We also explored genetic overlap between AD and CVD traits through proximity-based …

New Studies In Lattice-Based Cryptography, Quantum Algorithms, And Privacy-Preserving Computation, Hansraj Jangir

Electronic Theses and Dissertations

Classical public-key cryptographic schemes primarily rely on the presumed hardness of the integer factorization and discrete logarithm problems. However, Shor’s algorithm demonstrates that both problems can be solved efficiently on a sufficiently powerful quantum computer. This breakthrough motivated the search for quantum-resistant hard assumptions. The assumptions based on lattices are one of the primary candidates in post-quantum cryptography due to their strong theoretical foundations and well-established hardness against both classical and quantum attacks. In this thesis, we explore several directions of lattice based cryptology and quantum algorithms.

On the construction side, we propose two compact encryption schemes based on the …

Learning To See Lesions, Not Skin Tone: Counterfactual Multimodal Learning For Fair, Trustworthy, And Text-Free Dermatology Ai, Shivam Jangid

Master’s Dissertations

Recent advances in deep learning have significantly improved the performance of automated skin lesion classification systems, enabling accurate detection of various dermatological conditions from medical images. Despite these achievements, concerns regarding fairness and generalization remain a major challenge for the deployment of such systems in real-world clinical settings. A key factor contributing to these challenges is the presence of bias in training datasets, particularly with respect to skin-tone representation. Most publicly available skin lesion datasets contain a disproportionate number of samples from individuals with lighter skin tones. As a result, deep learning models trained on these datasets often learn representations …

Antioxidant Potential Of A Non-Heme Iron Complex: Mitigating H2O2-Induced Cellular Damage, Magy A. Mekhail, David M. Freire, Cameron Bowers, Grant Elam, Nora Del Bosque, Hannah K. Pyle, Sarah K. Dunn, Spencer Lanyon, Timothy J. Hubin, Giridhar Akkaraju, Kayla N. Green

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Iron complexes with antioxidant activity have garnered significant interest for both general and medical applications, yet few studies have yielded functional nonheme iron-based mimics for H₂O₂ mitigation in aqueous environments. Here, we investigate water-soluble nonheme iron complexes derived from 12-membered pyridinophanes (^CF₃PyN₃, PyN₃, ^NMe₂PyN₃, and Py₂N₂) to evaluate the impact of ligand scaffolds on H₂O₂ decomposition activity both in vitro and in a cellular model. Speciation and kinetic analyses reveal that both electronic and geometric modulation of the macrocyclic …

Trophic Transfer Of Fluorescent Polyethylene Microplastics In A Simplified Artemia–Oreochromis Aquatic Food Chain, Dativa J. Shilla

Tanzania Journal of Science

Microplastics (MPs) are pervasive contaminants in aquatic ecosystems, yet experimental evidence of their trophic transfer within tropical African food webs remains scarce. This study provides experimental evidence of indirect trophic transfer of microplastics from Artemia salina to Oreochromis urolepis, a cichlid species of ecological and economic importance in African inland and coastal waters. A simplified two-level food chain was established by exposing A. salina nauplii to fluorescent polyethylene microplastics (10–20 µm; 1, 10, and 100 mg L⁻¹) and subsequently feeding them to juvenile O. urolepis under controlled laboratory conditions. These concentrations were selected to represent a range of exposure levels …

Optimization Of Bio-Briquettes Production From Cassava Stems Co-Blended With Sisal Bole Bagasse Using Response Surface Methodology, Agnes Nshoma Msobi, Neema O. Msuya, Kando Khalifa Janga

Tanzania Journal of Science

This research aimed at producing bio-briquettes from cassava stems and sisal bole bagasse as an alternative source of cooking energy. A Response Surface Methodology (RSM) with Face - Centered Central Composite Design (FCCCD) featured a multi-objective optimization of the effect of the production parameters, focusing on maximizing char yield and Higher Heating Value (HHV) of the produced briquette while minimizing carbonization temperature and residence time. The findings showed that bio-briquettes produced at the lowest temperature (250 ℃) and residence time (30 min) and the blending ratio of 75% by 25% had the highest char yield of 76.92% and HHV of …

Pinnlab: An Interactive Dashboard For Teaching Data-Driven Parameter Estimation In Differential Equations Using Physics-Informed Neural Networks, Mohan J. Parthasarathy, Padmanabhan Seshaiyer

CODEE Journal

Undergraduate instruction in ordinary differential equations (ODEs) is typically organized around the forward problem: finding solution trajectories when the governing equation and its parameters are known. In scientific practice, however, inverse problems are often more relevant, requiring unknown parameters to be inferred from noisy observations while assessing whether a proposed model is consistent with the data. We introduce PINNLab, an open-source MATLAB dashboard designed to help undergraduate students explore inverse modeling through physics-informed neural networks (PINNs). PINNLab presents PINNs as a complementary data-driven framework that connects differential equations, optimization, empirical data, and scientific machine learning. The instructional sequence is organized …

The Dynamics Of Educational Change: A Complex Systems Perspective, Preethi Nanjundan, Lijo Thomas, Abith K. Sunil

Northeast Journal of Complex Systems (NEJCS)

The perception of university teachers toward educational reforms plays an important role in determining the success of changes introduced in the education sector. This study focuses on teachers’ attitudes toward change, their emotional responses, and their overall views on educational reforms. Across the world, many educational reforms have failed to achieve their expected outcomes in improving teaching practices and student learning. As education systems are highly complex, the approach toward implementing reforms has also changed over time. Some reforms are introduced gradually, while others involve major innovations within the system. Complexity theory provides useful insights and tools that help educators …

Towards Sustainable Marine Education: Assessing High School Students’ Understanding Of Conservation Concepts, Cheng-Chieh Chang, Tsuyoshi Sasaki, Ya-Yin Liao, Ling-Ya Hung, Liang-Ting Tsai

Journal of Marine Science and Technology–Taiwan

This study assesses the concepts of marine resource conservation and sustainability among Taiwanese high school students by developing a Chinese version of the Marine Resources Conservation and Sustainability Scale. Grounded in the cognitive, socio-emotional, and behavioral learning objectives outlined in UNESCO’s Education for Sustainable Development Goals (ESDGs), the scale targets students aged 16 to 18 to examine gender differences in marine knowledge and conservation concepts. The scale comprises 31 items across four dimensions: the first section evaluates marine knowledge, while the remaining dimensions utilize a four-point Likert scale to assess cognitive, socio-emotional, and behavioral learning objectives, respectively. The results indicate …

(Re)Claiming Homeplace: Dance As Embodied Resistance & Healing For Health & Spatial Justice, Preeya G. Kannan

University Honors Theses

This thesis argues that dance functions as both an upstream public health intervention and a form of radical spatial resistance; creating healing, agency, and belonging among historically marginalized communities. Drawing on bell hooks' concept of homeplace, Jasbir Puar's assemblage theory, Nancy Krieger's eco-social theory, and Katherine McKittrick's Black geographies, I position the body as both an ecological and political landscape shaped by histories of colonialism, racial capitalism, displacement, and resilience.

Through this community-based participatory research study, Homeplace, I explore dance as a form of social prescription that centers liberation rather than pathology. Movement is often reduced in public health discourse …

Gamma Belief Functions And Fuzzy Sets And Application To Combining Predictive Models, Liping Liu

University Research

Extending classic finite frameworks to continuous settings, this paper proposes the concept of gamma belief functions and gamma fuzzy sets. It shows that both the combination of gamma belief functions and the intersection of gamma fuzzy sets remain within the gamma family, enabling their application in combining gamma probability judgments in decision making and gamma regression models in ensemble learning. Using both simulated and real datasets, and under both constant and varying dispersion assumptions, experimental results show that the combined gamma regression models closely approximate the reference models learned from the full datasets, aligning with the objectives of bootstrapping. Notably, …

Engineering Nanoelectrocatalytic Systems For Co2 And Nitrate Conversion Into Value-Added Chemicals, Abdelrahman Mohamed Abdelmohsen

Theses and Dissertations

The thesis addresses two major related environmental crises: nitrate pollution of water systems and the ever-increasing levels of atmospheric carbon dioxide. Both challenges are closely linked to anthropogenic disturbance of nitrogen and carbon cycles and require sustainable, energy efficient mitigation techniques. In this study, we investigate electrochemical conversion routes as a unified approach to convert these pollutants into value-added compounds: ammonia (NH3) via nitrate reduction (NO3-RR) and ethylene (C2H4) via carbon dioxide reduction (CO2RR). The first half of this work deals with the design and engineering of Cu-Zn alloy electrocatalysts for efficient NO3-RR. Tuning the alloy composition and surface nanostructure …

Tuning Ion Mobility And Molecular Confinement In High-Performance Polymer Electrolytes For Energy Storage, Ezzeldien Yousef Muhammed Yousef

Theses and Dissertations

This research addresses the critical energy density limitations of aqueous supercapacitors, which are traditionally constrained by the narrow electrochemical stability window (ESW) of water 1.23 V. By employing two distinct molecular engineering strategies, this study developed high-performance electrolyte systems that significantly extend voltage stability and thermal resilience.

The first system, CsBr@PAM/HA, utilizes a polyacrylamide and hyaluronic acid hydrogel matrix. This system exploits the chaotropic nature of Cs⁺ ions to disrupt the aqueous hydrogen-bonding network, enhancing ionic conductivity to 104 mS cm^-1. Through systematic salt screening, CsBr was identified as the optimal electrolyte, enabling a stable 2.0 V …

Re: Comment Letter For Butte Priority Soils Operable Unit (Bpsou), Draft Intermediate (60%) Remedial Design Report, Blacktail Creek Riparian Actions (Dated March 13, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Examining The Impact Of The Palisades And Eaton Fires On Air Quality In Los Angeles, Ryan Edward Glenn

Earth Sciences Undergraduate Senior Theses

Wildland-urban-interface (WUI) fires in the US are increasing in frequency and intensity with disproportionately large impacts on air quality and human health. In January 2025, the Palisades and Eaton wildfires swept across the Los Angeles Basin, burning residential areas and destroying vegetation. Despite their significance, WUI fires remain understudied compared to wildland fires, especially in regard to emissions composition. Here, I utilize a combination of field samples, modeling, and remotely-sensed datasets to survey the emissions profiles and variations during the 2025 Palisades and Eaton wildfires. I find that 75.1% of Los Angeles County was exposed to surface PM2.5 rated ‘unhealthy’ …