Digital Commons Network^™

Quality Assurance Project Plan - Spokane River Pfas Study, Chad Pritchard

EWU PFAS Research Collection

Assessing the impacts of poly- and perfluoroalkyl substances (PFAS) contamination across multiple aquifers and multiple sources requires a detailed understanding of the hydrogeologic framework to quantifiably determine PFAS sources. The West Plains of eastern Washington is an ideal natural laboratory to study the fate and transport of PFAS because the general geohydrologic framework has been established and collaboration with several related PFAS projects will maximize the use of grant funds. This project will help the population, environment, and commercial entities of the West Plains by building a transport model, delineating PFAS contamination, and using unique PFAS distribution at different locations …

Resource Assessment Report No. 10: Southern Nearshore And Estuarine Scalefish Resource: Sandy Sprat (Whitebait) 2026 Assessment, Daniel E. Yeoh, Brett Crisafulli, Rubie Evans-Powell, Sybrand A. Hesp

Resource Assessment Reports

Sandy sprat Hyperlophus vittatus (‘whitebait’) is a small-bodied clupeid which occurs in temperate nearshore marine and estuarine waters throughout southern Australia. In Western Australia, this species is almost exclusively caught by the commercial sector on the lower west coast, between Perth and Geographe Bay, where it is considered to comprise a single biological stock. Since 2010, sandy sprat has primarily been caught by the South West Beach Net Fishery (SWBN) in the Bunbury region. This is a shore-based fishery which utilises beach seine nets to target a variety of finfish species in shallow nearshore waters.

Commercial catch is monitored and …

From Innovation To Impact: Evaluation Of The Shape Accelerator Cohort, Iryna V. Lendel, Chloe Wieber

Upjohn Institute Technical Reports

The Solutions Hub for an Alternative Packaging Ecosystem (SHAPE), a Michigan-Ohio partnership operated by the Michigan State University Research Foundation as part of a National Science Foundation Regional Innovation Engine, co-funded a special cohort of the NextCycle Accelerator focused on sustainable packaging and circular economy ventures. This report evaluates how the accelerator contributed to firm-level advancement and ecosystem-level change, drawing on program data and interviews with participating companies, program facilitators, stakeholders, and SHAPE management.  Participants most consistently credited coaching, network connections, and the Pitch Showcase with meaningfully impacting their business trajectory, gaining market traction, advancing technology readiness, and gaining access …

Quantum Mechanics, Non-Locality, And The Space Discreteness Hypothesis, Wilson A. Zuniga-Galindo

School of Mathematical & Statistical Sciences Faculty Publications

The space discreteness hypothesis asserts that the nature of space at short distances is radically different from that at large distances. Based on the Bronstein inequality, here, we use a totally disconnected topological space X as a model for the physical space at short distances. However, we consider the time as a real variable. In this framework, the Dirac–von Neumann formalism can be used. This discreteness hypothesis implies that given two different points in space, there is no continuous curve (a world line) joining them. Consequently, this hypothesis is not compatible with the theory of relativity. We propose R×(R×X)3 as …

Bridging Theory And Practice: A Data-Driven Community Partnership To Optimize Maintenance Effectiveness, Daniel Wu

Academic Affairs

This project established an immersive, industry-engaged learning experience that embedded Data Science students in a professional business environment through a partnership with Thiele Kaolin. Students applied advanced data mining, machine learning, and big data analytics techniques to large proprietary datasets to address authentic business challenges and generate actionable, data-driven insights. By working with complex real-world data, students bridged the gap between classroom theory and industry practice while gaining hands-on experience with the full data science workflow, including data preparation, exploratory analysis, predictive modeling, and results interpretation. The project also fostered critical thinking, teamwork, and professional competencies. Students collaborated in multidisciplinary …

Domain Knowledge-Informed Machine Learning Model To Study Weather-Induced Flight Delays, Gurvir Bawa

Doctoral Dissertations and Master's Theses

Weather-induced Traffic Management Initiatives (TMIs) occur rarely relative to normal air traffic operations. This scarcity produces severe class imbalance that limits predictive models of flight delay. To address it, this dissertation leverages a physics- and domain- knowledge informed Variational Autoencoder (VAE), conditioned on airport identity, that generates physically plausible synthetic weather events for underrepresented TMI categories. The fidelity of the model is assessed with a calibrated discrepancy measure disclosed along- side the results rather than described in free-form terms. A multitask Graph Neural Network (GNN) is then trained on the augmented dataset to jointly classify airport-level TMI status and predict …

Implementation Of The Problem-Based Learning Model On The Topic Of The Immune System To Enhance The Critical Thinking Skills Of Grade Xi B Students At Sman 1 Tojo, Nani Sofyanti, Sutrisnawati Sutrisnawati, Vita Indri Febriani, Mohammad Jamhari, Bustamin Bustamin, Raya Agni

Jurnal Pendidikan Sains

Critical-thinking skills are essential competencies for students in 21st-century learning. Preliminary classroom observations in Class XI B at SMAN 1 Tojo indicated that instruction remained predominantly teacher-centered and provided limited opportunities for students to engage in activities involving interpretation, analysis, evaluation, and inference. This study aimed to improve students’ critical-thinking skills through the implementation of Problem-Based Learning (PBL) on the immune system topic. The study employed a Classroom Action Research (CAR) design conducted over two cycles, involving 28 students in Class XI B. Data were collected using a teacher activity observation sheet and critical-thinking skills tests assessing four indicators: interpretation, …

Bioherbicidal Potential Of Noni Fruit (Morinda Citrifolia) Extract Against Water Hyacinth (Eichhornia Crassipes), Nur Rahma Afriani, Paulus Hengky Abram, Vanny M Agustina Tiwow, Reny Reny

Jurnal Pendidikan Sains

Noni fruit (Morinda citrifolia) contains secondary metabolites that may have potential bioherbicidal activity. This preliminary laboratory experiment aimed to identify flavonoids and tannins in noni fruit extract and to describe the phytotoxic responses of water hyacinth (Eichhornia crassipes) exposed to different extract concentrations. Noni fruit was extracted with 96% ethanol by maceration and concentrated using a rotary evaporator. The extract was qualitatively screened for flavonoids and tannins and applied to water hyacinth at concentrations of 0%, 10%, 20%, 30%, and 50% (v/v), with three plants per treatment. Plant responses were observed for 25 days and analyzed …

Evaluating The Nash Reaction As A Sustainable Alternative To The Snar Reaction In The Synthesis Of Pharmaceutical Intermediates, Allison L. Ryerson, James K. Bashkin, Jessica R. N. Thompson, Adam Weiss, Huy Q. Nguyen

Undergraduate Research Symposium

Nucleophilic aromatic substitution (SNAr) reactions are one of the most widely used reaction classes in pharmaceutical production today, used for example to produce nitroaryl amine intermediates. In comparison to the traditional SNAr pathway, the nucleophilic aromatic substitution of hydrogen (NASH) provides a greener alternative in pharmaceutical production by using cheaper starting materials, eliminating more hazardous solvents, and reducing toxic waste.

Synthesis And Charge Transport Characterization Of 9,9'-Bifluorenylidene-Based Conjugated Molecules For Single-Molecule Conductance, Zach Moughamian, Jahnavi Badiganti, Jinjia Xu

Undergraduate Research Symposium

Molecular electronics explores the use of individual molecules as functional components in nanoscale electronic devices. In this project, fluorenone-based π-conjugated molecules including 9,9'-bifluorenylidene-S and triphenylamine-substituted derivatives were synthesized to investigate structure-property relationships relevant to molecular charge transport. The synthesized compounds were obtained in 13% and 27% yield respectively. ¹H NMR spectroscopy confirms characteristic aromatic resonances in the 7-9 ppm region consistent with the conjugated framework. UV–Vis spectroscopy reveals absorption maxima at 459 nm and 470 nm, indicating extended π-conjugation and donor-acceptor effects. Single-crystal X-ray diffraction confirms the structure of 9,9'-bifluorenylidene-S, which crystallizes in the monoclinic system (space group P2₁/c). In …

Enantioselectivity Of The Photochemical Continuous-Flow Isomerization Of Humulones, Gregory M. Giovine, Trevor Smith, Bruce Hamper

Undergraduate Research Symposium

Humulones, the primary natural product present in the historically significant hop flower, represent a largely unexplored candidate for structure-based pharmaceutical design.  Showing promising biological activity as an anti-bacterial and anti-inflammatory agent, humulones are of interest both for their bioactive properties and for their long-established tolerability and natural abundance.  Humulones undergo a characteristic isomerization reaction, where the six-membered substituted phloroglucinol ring contracts to a five-membered ring isohumulone, under a variety of conditions, including those enabled by brewing conditions (thermal, metal-catalyzed) and by exposure to UV light.  Optimization of the photocatalyzed isomerization of n-humulone to n-isohumulone in flow conditions resulted in a …

Mapping St. Louis History: Slavery, Redlining, And The May 16th Tornado, Safa M. Altamimi, Aster Horbanova, Riley J. Bearden, Vivian B. Rhodes, Bridget Ragan

Undergraduate Research Symposium

For this project, our group members are traveling across St.Louis to areas that are affected by the May 16th tornado. We will be taking pictures and using ArcGIS survey123 to input data connecting the tornado to historical forces such as Redlining and Slavery. Using this data, we will be creating an ArcGIS StoryMap and presenting our findings.

Love And Artificial Intelligence: A Research Proposal, Bryanna M. Deatherage, Necdet Gurkan, Sandra J.E. Langeslag

Undergraduate Research Symposium

What happens when people fall in love with Artificial Intelligence (AI)? This study seeks to examine individuals who are in love with AI companions to gain a deeper insight in the cognitive and affective consequences. In addition, this study will examine the most effective forms of intervention regarding growing or reducing feelings of love toward AI. The first part of this study will be a questionnaire about the social and emotional impact of being in love with an AI companion. Three hundred participants will be recruited through online communities related to AI companions. The second part of this study will …

Butte Priority Soils Operable Unit Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 105 – Lizzie Shaft, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 129 – Heaney Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No 135 – Washoe Sampling Works, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit Final Butte Priority Soils Operable Unit Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 1503 – Hornet Addition, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Disturbance-Learning Inertia Estimation Using Artificial Neural Networks For Power System Stability, Sospeter Igaanja Gabriel, Francis Mwasilu, Peter Makolo Dr.

Tanzania Journal of Engineering and Technology (TJET)

ABSTRACT

Power systems are progressively shifting towards low inertia as a result of incorporating significant amounts of intermittent and converter-based renewable energy sources, such as wind and solar power, into the current power grid network. This integration poses considerable problems to inertia and frequency control within the network due to a reduction in the proportion of synchronous generators. Furthermore, rapid frequency deviations occur due to the disparity between supply and demand during contingencies, complicating the maintenance of frequency stability within the power system. The disturbance-learning inertia estimation method for power system stability is presented. The simulation analysis is performed using …

Gambaran Generasi Z Yang Kesepian Dalam Penggunaan Chat Ai Sebagai Pemenuhan Kebutuhan “Someone To Talk”, Ikhwanul Ihsan Armalid, Febty Zahra Arsiwi, Qisthi Fathiyyah, Ratri Mayzakky Afra Syahida

Jurnal Psikologi Sosial

This study aims to understand the experiences of Generation Z individuals who experience loneliness in utilizing Chat AI to fulfill their need for someone to talk to within a socio-emotional context. The study employed a qualitative approach using a phenomenological method involving six Generation Z participants aged 18 to 25 who had used Chat AI for emotional sharing or venting. Data were collected through semi-structured interviews and analyzed using thematic analysis. The thematic analysis yielded six main themes: the dynamics of Generation Z social interactions, experiences of loneliness in social life, patterns of Chat AI usage, Chat AI as a …

Bifurcation Dynamics Of A Harvested Predator-Prey Model, Hala H. Emam, Mohamed F. Abouelenein, Mona Anis, M. Y. Hamada, F. A. Atia, H. El-Metwally

Mathematical Modelling and Numerical Simulation with Applications

In ecosystems, the harvesting effect is essential to preserving the relationships between prey and predator. This work examines a model of predator-prey in discrete time with harvesting. The Jacobian matrix's eigenvalues are calculated for the associated fixed points. We examine the dynamical and qualitative analysis of this model, look into the criteria for stability and bifurcation, and analyze analytical results that show the rich dynamics and complexity of this model. We give sufficient circumstances for the Period-doubling at the interior equilibrium point by employing the harvesting effect. The discrete system's chaos control is carried out, and the outcomes are supported …

Emergence Of Purely Elastoplastic Turbulence In Shear Flows, Muhammad Abdullah, Shravan Pradeep, Doug J. Jerolmack, Becca Thomases, Paulo E. Arratia

Mathematics Sciences: Faculty Publications

Yield-stress fluids only flow above a critical stress. Here, we observe the emergence of a distinct, elasticity-driven flow state in a yield-stress fluid in the absence of inertia. Numerical simulations show that this elastoplastic turbulent state is characterized by non-Gaussian bimodal velocity distribution and a broad spectrum of velocity and stress fluctuations. Results show a nonmonotonic relationship between the volume fraction of the unyielded flow and plasticity. Surprisingly, the system can fluidize near the emergence of the elastoplastic turbulent state. Our results reveal the complex interplay between elasticity and plasticity in simple shear flows, indicating that plasticity can mobilize the …

Decision Support System For The Selection Of Thumbprint Recognition Algorithms In Biometric Security Systems, Toqeer Jameel, Muhammad Riaz

Neutrosophic Systems with Applications

This study investigates fingerprint recognition in immigration operations, emphasizing the role of biometric verification in enhancing security, fairness, and operational efficiency in international mobility. To address the uncertainty, vagueness, and imprecision inherent in fingerprint identification, a novel decision-making framework is proposed by integrating interval-valued picture fuzzy (IVPF) information. Fairly aggregation operators are introduced to combine decision makers' evaluations, while extracted fingerprint features are modeled using positive, neutral, and negative membership degrees within the IVPF environment. Objective criterion weights are determined using the criteria importance through intercriteria correlation (CRITIC) method, and individual ranking is performed via the alternative ranking order method …

A Data-Driven Neutrosophic Multi-Criteria Intelligent System For Functional Disability Severity Assessment, Ehab Abdel Aziz Al-Beblawi, Mirna Samy, Abduallah Gamal

Neutrosophic Systems with Applications

Functional disability assessment is a multidimensional problem because individuals may experience different levels of difficulty across daily activities such as walking, standing, dressing, eating, grasping objects, and social participation. This paper proposes NIFDA, a data-driven neutrosophic multi-criteria intelligent system for functional disability severity assessment. The proposed framework represents each functional response through three components: confirmed limitation, indeterminacy, and preserved functional ability. This allows the model to handle valid responses, uncertain information, and missing or non-informative data without forcing them into a single crisp score. To reduce dependence on subjective expert weighting, NIFDA derives criterion weights objectively using a hybrid CRITIC–MEREC …

Thermal Displacement Quantification And Dynamic Disparity Compensation For Automotive Stereo Cameras, Bisheng Wang, Xiyuan Hu, Ran Meng, An Jiang

Journal of System Simulation

Abstract: This paper presents a full-field thermal displacement inversion and dynamic disparity compensation method to address the disparity drift issue in mass-produced automotive-grade stereo cameras induced by thermal expansion and rigid-body displacement of image sensors under wide-temperature-range operating conditions. The proposed method leverages a high-precision static speckle pattern and digital image correlation (DIC) technique to achieve quantitative characterization of the nonuniform horizontal thermal deformation fields of the left and right image sensors. On this basis, a dynamic disparity compensation model is established, integrating a temperature-dependent quadratic polynomial translation term and a radial thermal expansion correction term. Experiments were conducted by …

Vehicle Cross-Modal Trajectory Prediction Model Based On Driving Style Hypergraphs, Guozhu Cheng, Changyuan Wang, Wenzhi Wang, Yifan Zhang, Tianjun Feng

Journal of System Simulation

Abstract: To address the shortcomings of existing motorway vehicle trajectory prediction methods which overlook differences in driving styles and the future interactions between trajectories of different modes. This paper proposes a cross-modal trajectory prediction model based on a dual-hypergraph Transformer for driving styles. The method first quantifies driving styles by extracting vehicle kinematic features and calculates a similarity matrix between vehicles; it then constructs a dual-hypergraph Transformer, using a homogeneous hypergraph to model the group interactions of vehicles with similar driving styles, and a heterogeneous hypergraph to capture the interaction relationships between spatially neighbouring but stylistically dissimilar vehicles; Finally, a …

Long-Tail Object Detection Method In Transportation Scene Images Based On Improved Rt-Detr, Mingjun Deng, Peihua Nie, Junhua Guo, Ningbo Gao

Journal of System Simulation

Abstract: Detecting rare objects in transportation environments is crucial for the safety and reliability of autonomous driving systems. To address the challenges of limited detection capability on rare objects that appear only a few times during training, we propose an improved long-tailed object detection method for traffic scene images named TF-DETR (tail free DETR) based on RT-DETR model. First, the lightweight CSP-EDA (CSP-efficient depthwise aggregation) was constructed to reconstruct the backbone network. Its core unit, the efficient depthwise aggregation, integrated the pooled-transpose attention and convolutional gated linear unit to enhance feature representations for tail-class samples. Second, the spatially-adaptive dynamic cognitive …

Vehicle Sar Image Simulation: Progress, Application And Challenge, Shengjie Luo, Zhigang Liu, Xihai Li, Yiting Wang, Xiaoniu Zeng, Xiaofeng Tan, Hongru Li, Tianyou Liu, Yun Zhang

Journal of System Simulation

Abstract: SAR image simulation technology can efficiently generate large-scale annotated data by flexibly configuring system parameters and scene conditions, breaking through the inherent limitations of high cost and long acquisition cycles associated with real SAR images, and effectively mitigating the problem of data scarcity. To elaborate on the overall research status of vehicle SAR image simulation, a classification framework for simulation methods is first established based on technical principles and methodological approaches. Subsequently, a comprehensive review of research progress is provided, offering an in-depth analysis of the theoretical foundations, practical applications, and suitable scenarios of various methods. Finally, based on …

Act Action Chunk Adaptive Optimization Method For Chemistry-Oriented Robots, Tan Li, Congying Wu, Shenghua Li, Nanjiang Chen, Weining Song, Fangfang Gao, Qi Wang, Yanwen Lin, Runmin Yin

Journal of System Simulation

Abstract: Chemical R&D laboratories face persistent challenges such as long R&D cycles and high experimental repetitiveness. With the growing demand for automation and intelligence in laboratory processes, embodied intelligent robots capable of learning expert operational experience and executing tasks stably in complex environments have become a key direction for improving chemical R&D efficiency and reducing human error. Although the hardware and software for embodied intelligence are advancing rapidly, current research focuses primarily on general-purpose operations, with limited attention to the specific constraints of chemistry laboratory settings. Traditional ACT algorithms, which use fixed action chunk sizes, fail to meet the requirements …

High-Dimensional Multi-Objective Optimization Algorithm Based On Large Language Model Assistance, Yichao Ma, Jingxuan Wei

Journal of System Simulation

Abstract: The increase in the dimension of objective functions in optimization problems makes it challenging to balance convergence and diversity in population-based algorithms, which is a key factor leading to performance degradation of multi-objective evolutionary algorithms. To address this issue, a dynamic switching mechanism assisted by a large language model is proposed. By continuously evaluating the changes in hypervolume and convergence metrics of the solution set, the search process is adaptively divided into three phases: convergence-oriented, diversity-oriented, and large language model-suggested phases, achieving precise allocation of computational resources. Furthermore, to mitigate the high computational cost of large language models in …

Modeling, Dynamical Analysis, And Lmplementation Of Switched Memristive Neural Networks, Zhuang Qu, Shaohua Zhang, Cong Wang, Hongli Zhang, Xinkai Li, Ping Ma

Journal of System Simulation

Abstract: To simulate the dynamic functional switching of brain networks, a time-switched memristive Hopfield neural network (TSM-HNN) model is proposed. The model utilizes external time-sequential signals to control memristive synapses, allowing it to dynamically generate multi-scroll chaotic attractors of varying numbers and morphologies without altering the system's structure. This overcomes the limitation of traditional chaotic systems, which can typically only produce a single type of attractor. The model exhibits complex chaotic behavior, high sensitivity to initial conditions, and coexisting attractors. Its physical feasibility has been verified through PSPice circuit simulations. This enhanced complexity and randomness give the model significant potential …