Digital Commons Network^™

Pedagogy On Teaching A Totally Blind Student Physical & Historical Geology & Labs, Kenneth R. Neuhauser

SACAD: Scholarly Activities

Teaching the salient points of both physical and historical geology and labs to a totally blind student was accomplished through pre-planning, extra staff, daily preparation, low-cost supplies, teamwork, and at times ‘on-the-spot’ creativity.

A New Highly Oxygen-Deficient And Cubic Pr3Zro8-Δ For Intermediate-Temperature Thermochemical Production Of Oxygen And Hydrogen, Jiaxin Lu, Yongliang Zhang, Luhong Chen, Yan Chen, Ke An, Yasser Shoukry, Xinfang Jin, Zhi-Hao Wang, Sai Mu, Kevin Huang

Faculty Publications

Two-step thermochemical cycles offer a clean route for hydrogen and oxygen production but are typically limited to high temperatures exceeding 1500 °C. Lowering operating temperatures would enable the use of alternative heat sources such as industrial waste heat. Here, we report Pr₃ZrO₈ as a new enabling material for efficient intermediate-temperature redox cycling, with thermal reduction at 900 °C in argon and steam oxidation at 400 °C. Pr₃ZrO₈ adopts a face-centered cubic structure similar to CeO₂ but exhibits significantly greater oxygen deficiency, achieving average oxygen and hydrogen fluxes of 331.7 and 70.3 µmol·g-1, respectively, …

Discrete Quantization On Spherical Geometries: Explicit Models, Computations, And Didactic Exposition, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

This article presents a comprehensive and analytically explicit study of optimal discrete quantization on spherical geometries equipped with the geodesic metric. Focusing on highly symmetric configurations on the unit sphere 𝕊2, we investigate three explicit models of discrete uniform distributions and derive closed-form expressions for their optimal quantizers and corresponding mean square quantization errors. (I) For N equally spaced points on the equator, we obtain exact error formulas for both divisible and non-divisible cases 𝑛 ∤𝑁, demonstrating that optimal Voronoi cells form contiguous arcs with midpoint representatives. (II) For two antipodally symmetric small circles at latitudes ±𝜙0, each with M …

Re: Approval Letter For The Final Repository Siting Study (Rss) Detailed Evaluation And Recommendations Report (Dated February 11, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Assessing The Geomechanical Modelling Of Underground Reservoir For Co₂ Storage Trapping Mechanisms, Bonavian Hasiholan, Mohammed Ali Farea, Elhassan Mostafa Abdallah, Sami Abdelrahman M. Yagoub, Yasir Mukhtar

Mathematical Modelling and Numerical Simulation with Applications

Effective carbon dioxide (CO₂) storage is essential for mitigating climate change amid increasing global greenhouse gas emissions. This study investigates the influence of geomechanics on CO₂ storage performance within carbon capture and storage (CCS), focusing on structural, residual, and solubility trapping mechanisms using a fully coupled modeling framework. Two numerical models, with and without geomechanical effects, are developed to evaluate impacts on reservoir behavior, CO₂ migration, and trapping efficiency. Each mechanism is analyzed separately and within an integrated framework to assess their combined contributions. Results indicate that geomechanical coupling increases reservoir pressure, reduces CO₂ flow velocity, enhances migration control, and …

A Coupled Fractional Thermistor System Demonstrating Existence, Uniqueness, And Simulation Results With Two-Point Boundary Conditions, Yahia Awad, Angela Khattar, Hussein Fakih, Sami Hammoud, Karim Amin

Mathematical Modelling and Numerical Simulation with Applications

This paper studies a coupled system of Caputo fractional differential equations of orders $\alpha, \beta\in(1,2]$, subject to two-point boundary conditions. The model incorporates nonlinear nonlocal integral terms that capture the memory-dependent interactions between thermal and electrical dynamics in thermistor materials. We rigorously establish existence via Schaefer’s fixed-point theorem and uniqueness through Banach’s contraction principle in a Banach space of continuous and continuously differentiable functions. Additionally, we analyze Ulam–Hyers stability to quantify solution sensitivity to initial perturbations. A numerical example highlights the effects of fractional orders and nonlocal feedback on system behavior. This work generalizes classical thermistor models and provides a …

E. The Michael Hofmann Seismic Sections - Part B, Michael H. Hofmann

1980 Flathead Lake Seismic Survey

This book contains a set  Images of the full seismic sections that were generated by Michael Hofmann in the early 2000s.  Links to the images follow the narrative by Robert W. Lankston.  This set of images relates to those lines that are not labeled on the track map in Figure 4C of the Kogan (1981) thesis.

Trends In Self-Reported Responses To Nutrition Facts Labels Before And After Nutrition Labeling Policy Implementation: A Comparison Of Adults In The United States And Mexico, Jim Thrasher Ph.D., Ma, Ms, Victor Vilalobos, Dai Fang, Alejandra Jáuregui, Alejandra Contreras-Manzano, Rachel Davis Ph.D., Lana Vanderlee, Christine M. White, Rachel B. Acton, James W. Hardin, Edward A. Frongillo Jr. Ph.D., Simón Barquera, David Hammond

Faculty Publications

Background

Objectives

Methods

D. The Michael Hofmann Seismic Sections -Part A, Michael H. Hofmann

1980 Flathead Lake Seismic Survey

A description of the process for constructing the full-length seismic sections from sets of scans of the paper field records made in the early 2000s by then PhD candidate Michael Hofmann.  Images of the full seismic sections follow the narrative by Robert W. Lankston.  This set of images relates to those lines labeled on the track map in Figure 4C of the Kogan (1981) thesis.

Unraveling Patch Size Effects In Vision Transformers: Adversarial Robustness In Hyperspectral Image Classification, Shashi Kiran Chandrappa, Sidike Paheding, Abel A. Reyes-Angulo

Michigan Tech Publications

Highlights: This work investigates the effect of spatial patch size on the classification accuracy and adversarial robustness of Vision Transformer-based architectures for hyperspectral image analysis. What are the main findings? Smaller patch sizes generally exhibit stronger adversarial robustness while maintaining comparable clean classification performance. Larger patch sizes tend to reduce robustness by increasing sensitivity to localized adversarial perturbations, with some dataset-dependent variations. What are the implications of the main findings? Spatial patch size is an important design consideration when applying Vision Transformers to hyperspectral image classification tasks. The findings provide practical guidance for informed patch-size selection in robust, deployment-aware transformer-based …

Magnetic Field Tuned Magnetic Order And Metamagnetic Criticality In Nonstoichiometric Ceaubi2, Halyna Hodovanets, Hyunsoo Kim, Tristin Metz, Yasuyuki Nakajima, Christopher J. Eckberg, Kefeng Wang, Jie Yong, Shanta R. Saha, David Graf, Nicholas P. Butch, Thomas Vojta, Johnpierre Paglione

Physics Faculty Research & Creative Works

We present a detailed study of magnetization, resistivity, heat capacity, and x-ray and neutron powder diffraction measurements performed on single crystals of nonstoichiometric CeAuBi₂, Au deficiency 18%, a strongly correlated antiferromagnet with Néel temperature T_N = 13.2 K. Field-dependent magnetization measurements reveal a large magnetic anisotropy at low temperatures with an easy axis along the crystallographic c axis, in which direction a spin-flop transition exhibits strong features in magnetization, specific heat, and resistivity at H_c = 75 kOe. The constructed temperature-field phase diagram connects this transition to the suppression of magnetic order, which evolves from a …

Uranium Chemical Compound Classification Using Sub-Images And Statistical Machine Learning For Nuclear Forensics, Lee C. Lambert, Brett J. Borghetti, Abigail A. Bickley

Faculty Publications

Uranium particle analysis from Scanning Electron Microscope (SEM) imagery is a crucial tool in nuclear forensics. The particle morphology lexicon proposed by Tamasi et al. in J Radioanal Nucl Chem 307, 1611–1619 (2016) follows a standardized, manual identification process to identify particle morphology features. The present work seeks to mirror this methodology using computer feature selection from the scikit-image Python library rather than human classification. Using a random forest classifier, a 56% overall uranium true positive classification accuracy (a 39.6% balanced classification accuracy) was achieved on a test set outperforming a naïve (chance) model by 48%. The methodology introduced splits …

Νgan: A Deep Learning Emulator For Cosmic Web Simulations With Massive Neutrinos, Neerav Kaushal, Elena Giusarma, Mauricio Reyes

Michigan Tech Publications

Understanding the impact of neutrino masses on the evolution of the Universe is a central goal of modern cosmology. Due to their large free-streaming lengths, neutrinos significantly affect structure formation at nonlinear scales, requiring accurate theoretical predictions to fully exploit current and future galaxy surveys. However, generating such predictions through large ensembles of cosmological simulations is computationally expensive. In this work, we introduce a deep learning-based generative adversarial network, νGAN, to emulate the Universe across a range of neutrino masses from 0.0 to 1.2 eV. The generated 2D cosmic web maps are statistically independent, show no correlations with the training …

Practices, Experiences, And Insights From Major Developed Economies On Green And Low-Carbon Technology Innovation Policies, Baihe Gu, Hongqian Wang, Yuling Sun, Dan Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

The transition toward green and low-carbon development has become a significant global trend for future growth. This study focuses on policy frameworks that support innovation in green and low-carbon technologies. It reviews the practices of major developed economies, such as the United States, the European Union, the United Kingdom, and Japan in this field, and synthesizes their experiences across key dimensions such as industrial policy, innovation actors, innovation ecosystems, funding mechanisms, and international cooperation. Drawing on these insights, and taking into account China’s unique advantages and challenges in green and low-carbon technological innovation, the paper offers policy recommendations aimed at …

Promoting Water Security Of South-To-North Water Diversion Project For National Water Network, Quanfa Zhang, Guihua Liu, Chesheng Zhan, Xiaobo Ren

Bulletin of Chinese Academy of Sciences (Chinese Version)

The South-to-North Water Diversion Project is a crucial infrastructure initiative aiming at optimizing nation-wide distribution of water resources, meanwhile fostering sustainable economic and social development, and ensuring the well-being of the people. The project, with its extensive scope and high technical complexity, particularly in the middle and west routes located in biodiversity hotspots such as the Qinling Mountains and the Qinghai-Xizang Plateau, may alter local microclimates, potentially triggering meteorological disasters such as droughts, thunderstorms, and hail, along with secondary hazards. The implementation of the project may also disrupt the local hydrological conditions, disturb the balance of the existing atmospheric-vegetation-soil system, …

Artificial Intelligence-Driven Materials Science: Evolution, Framework, Dilemmas, And Breakthroughs, Yanglili Zhou, Weihua Wang, Ziwei Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence-driven materials science (AIMS) represents a revolutionary and disruptive paradigm in materials research, promising to fundamentally break through the traditional bottlenecks of research cycles and efficiency. Historically, the evolution of materials science research paradigms from empirical trial and error, theoretical modeling, and computational simulation to the new data-driven stage has been driven by innovations in cognitive tools and methods. Currently, artificial intelligence, as a disruptive cognitive tool, is fundamentally reconstructing the core elements and interaction logic of materials science: the research process achieves intelligent iteration and full-process closed-loop; the capabilities of researchers are reshaped and teams are organized; and …

Study On Strategies And Measures And Insights For Introducing Artificial Intelligence Talents In Japan, Fangxin Hu, Ru Ma, Yujun Su

Bulletin of Chinese Academy of Sciences (Chinese Version)

In response to the aging population and the need for innovation in science and technology development, Japan regards AI as a key technology to solve social problems. In addition to accelerating the training of domestic AI talents, Japan is also vigorously introducing overseas AI talents. This study sorts out and analyzes Japan’s long-term, annual, and AI-specific strategic planning for the introduction of AI talents, including Basic Plan for Science, Technology and Innovation, Comprehensive Innovation Strategy, Strategic Plan for Artificial Intelligence Technology, and AI Strategy, and explores Japan’s specific implementation measures such as updating the national residence management system, improving the …

Https://Digitalcommons.Mtech.Edu/Superfund_Silverbowbutte/1787/, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Decolonial Approach To International Education: Insights From A Cal Poly Global Program In Palermo, Sicily, Elvira Pulitano, Iyad Jamaly

csuglobalaction

This article presents a critical intervention in the current debates about decolonizing international education. It is based on a Global Program in Palermo, Sicily, offered by Cal Poly San Luis Obispo in summer 2023. As both program creator/director and student participant in the program, the authors rely on their personal experience and insights along with expertise in coloniality and decolonial theories. The article focuses on a series of pedagogical activities led by a young group of migrants and refugees who, in the city of Palermo, have come together to form two associations designed and structured to offer new contemporary models …

Monitoring Strategies In Cave Microclimate Studies, Nenad Buzjak, Dalibor Paar, Aurel Persoiu, Christos Pennos, Franci Gabrovšek, Valerija Rossi

International Journal of Speleology

Cave atmospheres are spatially confined but dynamical systems that influence subterranean ecosystems, geomorphological processes, registration and preservation of climatic signals in sedimentary archives, cultural heritage, and conservation management. Despite major advances in cave climatology, methodological approaches to microclimate monitoring remain fragmented and are in some cases still shaped by the long-standing assumption that cave air temperature simply reflects the mean annual surface temperature. This paper revisits that assumption and develops an experience- and literature-based methodological framework for cave microclimate research. Key terminology is addressed by distinguishing between cave climate, cave microclimate, and cave meteorology, and by situating microclimatic variability within …

Cerebral Documents And Algorithmic Sensemaking: Searching For Expressions In Human And Artificial Cognitive Collaborations, Rebekah L. Cowell

Proceedings from the Document Academy

Generative Artificial Intelligences (AIs) and current advanced large language models (LLMs) are algorithmically designed to generate text-based conversations as conversational agents (CAs), by replicating human language and conversational communication. Pairing human cognition with generative computationally coded cognition. We have never been here before: cerebral and artificial information collaborations and processing producing expressions that may or may not become visible as second-hand/secondary source documents.

Sensemaking or sense(un)making is a unique autonomous human drive cognitively, our information processing is sensemaking in action and expressions and articulations are evidence of the sensemaking cycle. Documentation [expressed or articulated through various mediums] are a product …

Representing The Apparatus In Nineteenth And Twentieth Century Chemical Abstracting Literature, Evan F. Kuehn

Proceedings from the Document Academy

The rise of abstracting services in the 20th century is usually associated with the explosion of original scientific research and its attendant journal literature. The abstract was a tool of information dissemination and access for increasingly expansive and international work. What is often overlooked, however, is the correlation between original research and the technologies that made these advances available. Scientific apparatuses were, however, documented from the beginning, and were also a part of the rise of abstract literature in the 19^th and 20^th centuries. In this paper I examine the development of abstracts for apparatuses and patents in …

L. Dots To Data: Manufacturing Digital Seismic Traces From Scanned Images Of The Paper Sign Bit Sections From The 1970 Flathead Lake Seismic Survey, Robert W. Lankston

1970 Flathead Lake Seismic Survey

PowerPoint slides and the recorded audio of a lecture presented by Robert Lankston on October 13, 2014 in the University of Montana, Department of Geosciences Colloquium lecture series.

M. Epilogue For The 1970 Flathead Lake Seismic Project Collection, Robert W. Lankston

1970 Flathead Lake Seismic Survey

Re-introduction of the 1980 Qamar-Kogan seismic survey at Flathead Lake with recommendations for building an archive for that project. Article includes a proof-of-concept for converting scanned images of seismic sections recorded in variable density to digital seismic traces.

Ueof, Nick Truong, Pritam P. Karkomar, William J. Beksi

Event-Based Vision - Archive

UEOF is the first synthetic underwater event-based optical flow dataset derived from physically-based ray-traced RGBD sequences. It was constructed using a modern video-to-event pipeline applied to rendered underwater videos. It consists of realistic event data streams with dense ground-truth flow, depth, and camera motion. The dataset is composed of 12 minutes and 51 seconds of data across 13,714 RGB frames. This results in a total of 4.94 billion events across all scenes. UEOF exhibits a high dynamic range of motion with a mean flow magnitude of 6.1 px and a median of 3.6 px. The motion distribution is heavy-tailed. While …

A Transcriptional Program Associated With Neurotransmission In The Living Human Brain, Alexander W. Charney, Lora E. Liharska, Eric Vornholt, Alissa Valentine, Anina Lund, Alice Hashemi, Ryan C. Thompson, Terry Lohrenz, Jessica S. Johnson, Nicole Bussola, Esther Cheng, You Jeong Park, Salman Qasim, Alisha Aristel, Lillian Wilkins, Kimia Ziafat, Hannah Silk, Lisa M. Linares, Brendan Sullivan, Claudia Feng, Beniamino Hadj-Amar Ph.D.

Faculty Publications

At the foundation of neurotransmission, and by extension at the foundation of brain function, are coordinated programs of gene expression involving many thousands of genes. These programs are poorly defined in humans because most modern studies that characterize human brain gene expression use tissue obtained in the postmortem state when neurotransmission and brain function have ceased. Here, to advance knowledge of the gene expression programs at the foundation of neurotransmission in the human brain, gene expression was characterized in 130 prefrontal cortex (PFC) samples obtained from participants of the Living Brain Project (LBP) during neurosurgical procedures in conjunction with intracranial …

Survival On Image Regression With Application To Partially Functional Distributional Representation Of Physical Activity, Rahul Ghosal, Sunwoo Emma Cho, Marcos Matabuena

Faculty Publications

Technological advancements in wearable devices and medical imaging often lead to high-dimensional physiological signals in the form of images or surfaces. To address these data structures, we develop a novel survival on image regression model with a specific focus on partially functional distributional representation of wearable data. The existing approaches for functional data and survival outcomes have been primarily developed for uni-dimensional functional predictors. Drawing on recent developments in distributional data analysis, we model temporally varying distributional patterns of physical activity (PA) as a partially functional distributional predictor within a semiparametric Cox model framework. We use tensor product splines to …

Environmental Chemicals And Maternal Depression During And After Pregnancy: A Scoping Review, Pengfei Guo, Yunyue Shi, Cindy Nguyen, Haoran Zhuo, Tormod Rogne, Zeyan Liew

Faculty Publications

Purpose of Review

There is increasing evidence that several environmental exposures may pose a risk for depression, including maternal depression. We conducted a scoping review of epidemiological evidence regarding maternal exposure to environmental chemicals and perinatal depression.

Recent Findings

We searched PubMed, Embase, Web of Science, Dimensions, and Scopus, and summarized the findings from 27 articles that examined environmental chemical exposures and maternal depression. Studies of ambient air pollutants (N = 11) showed exposure to NO₂ and PM10 to be most consistently associated with antenatal or postnatal depression. Studies of endocrine-disrupting chemicals, including phthalates (n = 6), …

2026 February 19 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Ai-Guided Binding Mechanisms And Molecular Dynamics For Mers-Cov, Pradyumna Kumar, Lingtao Chen, Rachel Yuanbao Chen, Yin Chen, Seyedamin Pouriyeh, Progyateg Chakma, Abdur Rahman Mohd Abul Basher, Yixin Xie

Faculty Articles

The MERS-CoV (Middle East respiratory syndrome coronavirus) is a zoonotic virus with a high mortality rate and a lack of antiviral drugs, underscoring the need for effective therapeutic methods. Viral entry depends on interactions between viral surface proteins and human receptors, with Dipeptidyl Peptidase-4 (DPP4), a transmembrane glycoprotein, acting as the receptor for MERS-CoV. We employed Molecular Dynamics (MD) Simulations to identify critical interface residues under a high-performance computing (HPC) workflow for accelerated results. Target residue pairs were identified through analysis of salt bridge and hydrogen bond occupancy. The stability of these residues was confirmed through three independent MD Simulations …