Digital Commons Network^™

Mgrre_Thinsections_Mgrre_11_2, Mgrre

Thin Sections

No abstract provided.

Managing Collaboration Under Conservation Crisis: Trust, Risk, And Control In The Gulf Of Maine Fishery Management Network, Evelyn Roozee, Owen Temby, Dongkyu Kim, Antonia Sohns, Anthony Rocha Lima, Jasper R. De Vries, Gordon M. Hickey

School of Earth, Environmental, & Marine Sciences Faculty Publications

Transboundary fishery management and the intertwined conservation of critically endangered species represent significant governance challenges that require ongoing inter-organizational communication, collaboration, and collective action to achieve shared objectives. Previous research suggests that inter-organizational collaborative performance depends heavily on different dimensions of trust and complementary control mechanisms to mitigate the perceived risks of collaborating and enable the reciprocal sharing of resources and the coordination of activities. However, it is unclear how proposed relationships between trust, risk, and control are shaped by disruptions to established transboundary management networks. This study presents the results of survey research conducted in the Gulf of Maine …

Optimizing Multi-Layer/Multi-Physics Passive Adaptive Thermal Enclosures For Climate-Responsive Energy Regulation: A Numerical Study, Rajae Bousselham, Mingjiang Tao, Sergio Granados-Focil, Adriana Hera, Steven Van Dessel

Chemistry

Adaptive facades regulate heat transfer by adjusting their thermal behavior in response to environmental conditions. Passive adaptive systems, including stimuli-responsive thermal storage materials, tunable radiative coatings, and variable-conductivity layers, offer significant potential for material-based thermal regulation. However, their combined potential remains unexplored, as most studies examine individual mechanisms in isolation. As a result, trade-offs among energy savings, material usage, design complexity, and climate responsiveness are often underrepresented, overlooking coupled interactions in multilayer assemblies limiting their effectiveness. This study develops a transient three-dimensional numerical framework coupling heat transfer with multi-objective optimization to evaluate trade-offs between minimizing annual energy consumption and enclosure …

A Review Of Gallium And Germanium Recovery From Industrial Solid Residues, Ernest V. Oteng, Marthias Silwamba, Lana Alagha, Alex Luyima

Mining Engineering Faculty Research & Creative Works

The global demand for critical elements such as gallium (Ga) and germanium (Ge), and the shift toward circular mining has accelerated the development of new extraction and recovery processing these metals from industrial solid residues. This transition is driven by a substantial surge in demand for advanced technologies and the depletion of primary ore. Consequently, industrial solid residues, particularly zinc processing residues, smelter slags, flue dusts, and coal fly ash, are emerging as viable alternative sources. These residues incorporate Ga and Ge through isomorphic substitution in phases such as ferrites, silicates, and glassy aluminosilicates, and are enriched by industrial processes, …

Glomalin-Related Soil Protein In Colluvial Soils As A Proxy For Reconstructing Millenary Changes In Landscape And Soil Health, Axel Werner, Lourdes López-Merino, Joeri Kaal, Cruz Ferro-Vázquez, Oscar Serrano

Research outputs 2022 to 2026

Glomalin-related soil protein (GRSP) is an operationally defined soil organic matter pool that includes a heat shock protein linked to arbuscular mycorrhizal fungi (AMF) living in symbiosis with most vascular plants and plays a key role in soil health. However, the potential of GRSP as a palaeoecological proxy remains unexplored. We analysed the GRSP content in a North-western Iberian colluvial soil profile encompassing the last 14,000 years. We aimed to 1) identify whether GRSP is preserved, and 2) investigate whether GRSP could be used as a palaeoecological proxy after comparing its record with palynological and pedoanthracological records that account for …

The Unacknowledged Challenge Of Moral Distress For Nurse Academics, Adam Burston, Glenna Mae Guiriba, Meena Gupta, Sara Bayes

Research outputs 2022 to 2026

The pluralistic nature of healthcare presents nurses with situations challenging their moral values which nurses must navigate. Challenges to moral values can result in the experience of moral distress, a problem that is common within the clinical nursing context. Moral distress is a known and well-researched phenomenon within nursing and has long contributed to detrimental effects such as frustration, anger, anxiety, decreased job satisfaction, burnout and ultimately attrition. However, despite extensive research in clinical environments, minimal research exists detailing this concept within the context of nursing academics and educators. Nurses can experience moral distress if they are in or exposed …

Defense-To-Attack: Bypassing Weak Defenses Enables Stronger Jailbreaks In Vision-Language Models, Yunhan Zhao, Xiang Zheng, Yige Li, Xingjun Ma

Research Collection School Of Computing and Information Systems

Despite their superb capabilities, Vision-Language Models (VLMs) have been shown to be vulnerable to jailbreak attacks. While recent jailbreaks have achieved notable progress, their effectiveness and efficiency can still be improved. In this work, we reveal an interesting phenomenon: incorporating weak defense cues into the attack pipeline can significantly enhance both the effectiveness and efficiency of jailbreaks on VLMs. Building on this insight, we propose Defense2Attack, a novel jailbreak method that bypasses the safety guardrails of VLMs by leveraging defensive patterns to guide jailbreak prompt construction. Specifically, Defense2Attack consists of three key components: (1) a visual optimizer that embeds universal …

Tiny Large Language Models For Iot Networks: Potentials And Challenges, Muhammed Golec, Suhib Bani Melhem, Yaser Khamayseh, Abdulmalik Alwarafy, Naofal Al-Dhahir

All Works

Large Language Models (LLM), which have gained great momentum in recent years, have revolutionized the field of Artificial Intelligence (AI); while their applicability for hardware-constrained Internet of Things (IoT) environments has begun to be questioned. This has led to the emergence of compact architecture and resource-efficient Tiny LLM models. This survey paper systematically examines Tiny LLMs for IoT networks and classifies existing approaches in five basic dimensions: model architectures, optimization strategies, transfer learning methods, deployment paradigms, and explainability-security integration. By applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, 139 related studies published between 2020 and 2025 …

Effects Of Demineralization Protocols On Hydrogen And Oxygen Isotope Ratios In Fossil Bone Collagen, Linda M. Reynard

Boise State University Publications and Presentations

The effect of three commonly used preparation protocols on bone collagen δ2H and δ18O values was investigated, using six generally well-preserved faunal bones (cattle, bison, horse) ranging in age from the Holocene to Late Pleistocene. The treatments tested were ethylene diamine tetraacetic acid demineralization without gelatinization and hydrochloric acid demineralization with and without gelatinization. There are significant shifts in δ18O values among preparation methods. No systematic shifts in bone collagen δ2H values were noted among the three treatments, and most offsets were low (< 2–3 ‰) and smaller than typical measurement uncertainties. A few sample/treatment combinations yielded slightly higher inter-treatment δ2H differences (∼ 5–7 ‰). Lower mass fraction of hydrogen in …

The Relationship Between Anaphylatoxin Receptors, T Cell Polarization, And Vascular Inflammaging, Kathryn D. Hok

Summer Research Program Abstracts

No abstract provided.

Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …

Keyframe Selection From Motion Capture Data With Dual-Agent Reinforcement Learning, Kun Hu, Wang, Clinton Mo, Mingyang Ma, Shaohui Mei, Zebin Chen, Zhiyong Wang

Research outputs 2022 to 2026

Animation production workflows centered around motion capture techniques require animators to edit motions based on a set of keyframes. However, most existing keyframe selection methods are optimization-based, which suffer from the issues of flexibility and efficiency. In this paper, a novel deep reinforcement learning method with dual agents are proposed for unsupervised keyframe selection. First, an S-Agent and an R-Agent evaluate the actions of selection and refinement, respectively. A deep spatio-temporal network, namely graph keyframe evaluation network (GKEN), is proposed for the agents. Then, an animation specified reward is devised based on reconstruction, which fulfills three important properties of the …

Analyzing Developer Discussions On Eu And Us Privacy Legislation Compliance In Github Repositories, Georgia M. Kapitsaki, Maria Papoutsoglou, Christoph Treude, Ioanna Theophilou

Research Collection School Of Computing and Information Systems

Context: Privacy legislation has impacted the way software systems are developed, prompting practitioners to update their implementations. Specifically, the EU General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have forced the community to focus on users’ data privacy. Objectives: Relying on the vast amount of data on developer issues available in GitHub repositories, our aim is to gather empirical evidence on the issues developers of Open Source Software discuss to comply with privacy legislation. Method: We examined such discussions by mining and analyzing 32,820 issues from GitHub repositories. We partially analyzed the dataset automatically to identify …

Semantic-Structural Decoupling: Disentangling Semantic Attention From Structural Bias In The Attention Manifold, Pengkun Jiao, Bin Zhu, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

The empirical success of attention mechanism in Multimodal Large Language Models (MLLMs) often obscures its inherent, subtle flaws. Specifically, MLLMs consistently exhibit disproportionate attention toward certain semantically uninformative visual tokens, a phenomenon termed "register" or "Visual Attention Sinks." While existing inference intervention methods attempt to identify these sink tokens and redistribute their attention weights, such approaches typically treat these tokens in isolation and suffer from computational inefficiency. Instead, we reframe this phenomenon as a generalized textual bias exerted over visual features that extends beyond isolated sink tokens. From this perspective, a pervasive structural bias leads to the dilution of the …

Spatialimaginer: Towards Adaptive Visual Imagination For Spatial Reasoning, Yian Li, Yang Jiao, Bin Zhu, Tianwen Qian, Shaoxiang Chen, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Spatial intelligence, which refers to the ability to reason about geometric and physical structure from visual observations, remains a core challenge for multimodal large language models. Despite promising performance, recent multimodal large language models (MLLMs) often exhibit fragile reasoning traces in spatial intelligence tasks that involve consistent spatial state recognition. We argue that these failures stem from a mismatch between the spatial recognition mechanism and the text-only reasoning behavior of these MLLMs. Effective spatial reasoning requires low-level geometric structure to be faithfully preserved and updated throughout the reasoning process, whereas textual representations tend to abstract away precisely these critical details. …

Mind The Hazard: Modeling And Interpreting Comfort With Personalized Sensing, Yufei Zhang, Matteo Favero, Patrick Chwalek, Sailin Zhong, Denis Lalanne, A. Joseph Paradiso, Clayton Miller, Andrew Sonta

Research Collection College of Integrative Studies

Recent advances in personalized sensing and comfort feedback have spurred the development of data-driven comfort models tailored to individual needs. However, because current models treat sequential comfort feedback independently, they are subject to unstable predictions and limited interpretability, hindering their deployment in building management. This study introduces a dynamic modeling framework that utilizes a Neural Ordinary Differential Equations-based Continuous-time Markov Chain to model the transitions in comfort states over time. Our modeling approach, developed through a field study utilizing smart glasses and mobile app feedback, tracks occupants' comfort transitions across daily activities and contexts. The results demonstrate that this model …

Pattern Formation In Quantum Hierarchical Cellular Neural Networks, Wilson A. Zuniga-Galindo, B. A. Zambrano-Luna, Chayapuntika Indoung

School of Mathematical & Statistical Sciences Faculty Publications

We present a new class of quantum neural networks (QNNs) whose states are solutions of p -adic Schrödinger equations with a non-local potential that controls the interaction between the neurons. These equations are obtained as Wick rotations of the state equations of p -adic cellular neural networks (CNNs). The p -adic CNNs arise as continuous limits of large discrete hierarchical neural networks (NNs). The CNNs are bio-inspired by the Wilson–Cowan model, which describes the macroscopic dynamics of large populations of neurons. We provide a detailed study of the discretization of the new p -adic Schrödinger equations, which allows the construction …

A Finite Element Model For Thermomechanical Stress-Strain Fields In Transversely Isotropic Strain-Limiting Materials, Saugata Ghosh, Dambaru Bhatta, S. M. Mallikarjunaiah

School of Mathematical & Statistical Sciences Faculty Publications

This paper presents a comprehensive computational framework for investigating thermo-elastic fracture in transversely isotropic materials, where classical linear elasticity fails to predict physically realistic behavior near stress concentrations. We address the challenge of unphysical strain singularities at crack tips by employing a strain-limiting theory of elasticity. This theory is characterized by an algebraically nonlinear constitutive relationship between stress and strain, which intrinsically enforces a limit on the norm of the strain tensor. This approach allows the development of very large stresses, as expected near a crack tip, while ensuring that the corresponding strains remain physically bounded. A loosely coupled system …

Emotional Urgency And Lack Of Perseverance Are Linked To Anxiety Sensitivity And Improve During Early Recovery From Opioid Use Disorder., Breanna A. Mcnaughton-Long, Abigail J. Pleiman, Carmen Buchfink, Chrysantha B. Davis, Rayus Kuplicki, Martin P. Paulus, Hung-Wen Yeh, Maëlle C M Gueguen, Jennifer L. Stewart

Manuscripts, Articles, Book Chapters and Other Papers

Few studies have identified how facets of impulsivity relate to recovery in opioid use disorder (OUD). Treatment-enrolled individuals with OUD (n = 167) and healthy controls (CTL; n = 46) completed the Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency (UPPS-P) Impulsive Behavior Scale along with demographic and clinical measures at visit 1. Over the next three months, abstinence and return to use were documented for participants with OUD (via self-report, alcohol breathalyzer, urine drug screen, and secondary contact communication). Participants with OUD who returned to use (n = 59) did not complete further study visits, whereas those who remained abstinent …

Mgrre_Thinsections_Mgrre_11_1, Mgrre

Thin Sections

No abstract provided.

The Impact Of Social Determinants Of Health On Length Of Stay For Neonates Discharged With Feeding Support From The Neonatal Intensive Care Unit (Nicu), Claire C. Hockett

Summer Research Program Abstracts

No abstract provided.

Pentagonal Pdte2 Monolayer For Sustainable Solar-Driven Hydrogen Production, Narender Kumar, Shambhu Bhandari, Dario Alfè, Ravindra Pandey, Nacir Tit

Michigan Tech Publications

This investigation demonstrates that the pentagonal PdTe2 (penta-PdTe2) monolayer is a highly tunable two-dimensional (2D) photocatalyst, characterized by the bandgap of 1.87 eV and high hole mobility. Using density functional theory calculations with the HSE06 functional, we show that tensile strain engineering (particularly at +2% and +3%) is essential for enabling spontaneous water splitting. At these strain values, the valence-band maximum and conduction-band maximum straddle the water redox potentials (H+/H2 and O2/H2O) under both acidic (pH = 0) and neutral (pH = 7) conditions. The monolayer's low hole effective mass facilitates rapid charge extraction, mitigating recombination and driving the oxygen …

Patellofemoral Alignment Following Total Knee Arthroplasty: A Radiographic Analysis Of 300 Patients With Two Implant Designs, Giselle K. Henry

Summer Research Program Abstracts

No abstract provided.

Adaptive Improved Particle Swarm Optimization-Based Maximum Power Point Tracking And Energy Smoothing For Photovoltaic Hybrid Battery–Supercapacitor Storage Systems, Mohammad Aminul Islam, Guo Shaokai, Jakaria Mahdi Imam, Mohammad Khairul Basher, Nowshad Amin, Tarek Abedin, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

The rapid development of photovoltaic (PV) systems has made them an important component of the global clean energy strategy. However, the intermittency and non-linear characteristics of photovoltaic (PV) output remain major challenges for stable renewable energy utilization. This study proposes an adaptive improved particle swarm optimization (IPSO)-based maximum power point tracking (MPPT) strategy integrated with hybrid energy storage coordination for photovoltaic systems. The IPSO introduces adaptive inertia adjustment, velocity clamping, and stagnation reinitialization, which improve the convergence robustness under dynamic irradiance and temperature conditions. The algorithm was benchmarked against Perturb & Observe (P&O), Incremental Conductance (INC), and standard PSO using …

Defining Rectus Abdominus Muscle Changes Following Ventral Hernia Repair, Ananya Hari

Summer Research Program Abstracts

No abstract provided.

Assessor Experiences In Cmmc Level 2 Certification Assessments: An Interpretative Phenomenological Analysis Of Role Expectations, Samuel Heuchert, John Hastings

Research & Publications

The Cybersecurity Maturity Model Certification program requires that third-party assessments be conducted under a non-consultative model. The model is intended to ensure impartiality for organizations seeking certification. While this structure defines expectations for assessor behavior, assessor experiences and interpretations of these constraints remain underexamined. The study examines the lived experiences of CMMC-Certified Assessors and how they navigate role expectations within the non-consultative model. Using Role Conflict Theory as a guiding framework, the study applied Interpretative Phenomenological Analysis (IPA) to semi-structured interviews to explore how assessors make sense of their roles. The analysis identified experiential themes that describe how assessors construct …

Taste Matters: Designing And Testing A Nurse-Led Intervention In Oncology, Sharon Kilbride, Abigail Dillon, Bree Aguilar, Mary Hook

Nursing

Problem/Research Question: Taste alteration affects up to 70% of oncology patients receiving chemotherapy, leading to decreased dietary intake, malnutrition, and poor quality of life. It is often under reported due to lack of taste assessments during toxicity screening and has no known treatment. Researchers have shown that breast cancer patients were able to assess and control alterations with a researcher-delivered intervention. Research is needed to translate this promising strategy for clinical use with populations beyond breast cancer.

Objectives: An oncology-certified infusion nurse observed that many chemotherapy patients experienced taste alterations that affected their quality of life. The observations sparked interest …

Maternal Characteristics And The Social Determinants Of Health In Fetal Vs Postnatal Myelomeningocele Repair, Amy Rose Hardcastle

Summer Research Program Abstracts

No abstract provided.

Fall 2026 Environmental Sciences Seminar Series, Sam Bogan, Sam Bogan

NRESS Seminars

The deep sea is Earth's largest and least-explored habitat, leaving much of its biology unknown. I will present two studies leveraging long-read sequencing to uncover the population dynamics and evolution of deep-sea vertebrates. First, we examined how deep-sea invasions constrained thermal adaptation in  globally distributed fishes. Second, we reconstructed the demography and population health of elusive, deep-foraging whales. In these intractable but important systems, advances in long-read sequencing enabled previously unattainable biological insights.

Fall 2026 Environmental Sciences Seminar Series, Wenjing Xu, Wenjing Xu

NRESS Seminars

Animal movement is fundamental to biodiversity, offering early signals of species' responses to environmental change. I first discuss how wildlife movement is shaped by landscape composition and configuration, from global to local scales. I then focus on one linear infrastructure reconfiguring landscapes worldwide: fences. Drawing on research from the western US and beyond, I show how fences reshape animal movement, with cascading consequences for ecosystems and societies. I close with reflections on broadening this science through visual storytelling.