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Documents From The January 31. 2024 Meeting Of The Associated Students Of The University Of Montana (Asum), University Of Montana--Missoula. Associated Students
Documents From The January 31. 2024 Meeting Of The Associated Students Of The University Of Montana (Asum), University Of Montana--Missoula. Associated Students
Senate Meeting Agendas and Minutes, 2007-Present
Agenda and meeting minutes from the January 31, 2024 meeting of the Associated Students of the University of Montana (ASUM).
Domain Switch On Sentiment Analysis Using Gradient Reversal Layer, Hemish Veeraboina
Domain Switch On Sentiment Analysis Using Gradient Reversal Layer, Hemish Veeraboina
Master's Projects
Switching domains in sentiment analysis presents the challenge of transferring learned knowledge from one context to another without the need to label data. Traditional methods often struggle when dealing with differences in data distribution a problem known as the domain shift issue. To tackle this using Gradient Reversal Layers (GRL) has emerged as a solution for adapting to different domains in an unsupervised learning setting. This study introduces an enhancement to the standard GRL approach by incorporating a sigmoid function that gradually adjusts how intensely domain adaptation occurs during training. This upgraded GRL technique ensures controlled learning outcomes making it …
Emotion Detection Using Ensemble Learning, Priya Harika Yerapothu
Emotion Detection Using Ensemble Learning, Priya Harika Yerapothu
Master's Projects
Emotion detection is gaining exponential necessity in today’s technological age. This research seeks to delve into ways conversational AI could be enhanced by integrating emotional intelligence using an ensemble learning approach. Traditional machine learning along with advanced neural network architectures are implemented to improve the understanding and intricacies of emotion detection from textual data. The dataset we use is GoEmotions dataset, annotated with 27 emotional labels, to conduct a detailed analysis of emotion recognition. Various machine learning models, such as HistGradientBoosting, LightGBM, CatBoost, and MLP, will be evaluated side by side with advanced models of Bidirectional Long Short-Term Memory (BiLSTM) …
Optimized Community Detection Across Distributed Heterogeneous Servers, Akash Narang
Optimized Community Detection Across Distributed Heterogeneous Servers, Akash Narang
Master's Projects
The exploration of community detection is crucial across various fields, including marketing, and biological research. This area has evolved from non-overlapping communities to recognize nodes as part of multiple overlapping communities. Current research continues to uncover these dynamics. The main challenge is identifying overlapping communities in graphs with billions of nodes and edges. This paper aims to enhance methodologies for community detection in parallel for unprecedentedly large and complex networks. We introduce the HeteroNodesAdapter algorithm, which supports heterogeneous worker nodes and optimized load distribution in graph stream processing. Additionally, we propose the TailBalancedCommunitySize algorithm to find an optimum community size, …
Community Detection Using Deep Learning: Variational Graph Autoencoder Enhanced With Leiden And K-Truss Techniques, Jyotika Hariom Patil
Community Detection Using Deep Learning: Variational Graph Autoencoder Enhanced With Leiden And K-Truss Techniques, Jyotika Hariom Patil
Master's Projects
Community detection in networks is essential for understanding the complex structures of connected systems. Traditional deep learning (DL) methods such as Graph Neural Networks (GNNs) and Graph Convolutional Networks (GCNs) have shown promised results in supervised tasks, like classification, but often fail in unsupervised tasks like community detection because of the lack of labels. Self- supervised approaches where we integrate crucial community information offer a solution. This project seeks to explore DL methods for community detection, focusing specifically on using Graph Variational Autoencoders (VGAEs). While classical approaches can efficiently handle small to medium-sized networks, they typically struggle with larger-sized structures. …
Influence Maximization Using Triadic Closures, Communities, And Quotas, Matthew Fu
Influence Maximization Using Triadic Closures, Communities, And Quotas, Matthew Fu
Master's Projects
Online social networks have exploded in popularity in the last decade. In addition, traditional advertising methods such as television advertising have greatly decreased. This allows companies to utilize viral marketing more effectively. With viral marketing, companies can spread information on a product to a social network by reaching out to a small group of early adopters, who will go on to inform the people around them of the product. The problem is selecting the early adopters that can maximize the spread of influence. The Influence Maximization (IM) problem is finding a social network’s most influential (early adopters) starting nodes, called …
Characterizing Nanopore Sequencing Artifacts With Deep Learning, David Zhou
Characterizing Nanopore Sequencing Artifacts With Deep Learning, David Zhou
Master's Projects
Oxford Nanopore sequencing is a revolutionary new technology for sequencing DNA molecules in long stretches. However, it has a significantly higher error rate than conventional short-read sequencing, resulting in numerous sequencing artifacts. These artifacts can be indistinguishable from low frequency somatic variants, which is a roadblock for cancer diagnosis using liquid biopsies. In this study, benchmarked human genome samples from Genome in a Bottle were used to create a dataset of labeled variants, including artifacts and true variants. Variant features, including sequence context, were used to train various deep learning models. The multi-input neural network combining sequence context features and …
Employing Large Language Models And Retrieval Augmented Generation For Enhanced Predictive Flexibility In Cancer Mortality Prediction, Mridang Kejriwal
Employing Large Language Models And Retrieval Augmented Generation For Enhanced Predictive Flexibility In Cancer Mortality Prediction, Mridang Kejriwal
Master's Projects
Today, cancer is a major health risk to thousands of people, and there are over a two-hundred different types of cancer. Luckily, over the past several years, the outcomes and survival rates have increased, all thanks to machine learning, specifically Recurrent Neural Networks (RNN) and Long Short-Term memory (LSTM) networks. However, the current prognostic models don’t allow healthcare professionals to adapt the variables to mimic all the different features of every type of cancer, resulting in a model that works but is not as accurate as it could be. This study explores improving the accuracy and adaptability of the current …
Temporal Dynamics In Diabetes Prediction: A Sensor-Driven Time-Series Exploration, Monica Meduri
Temporal Dynamics In Diabetes Prediction: A Sensor-Driven Time-Series Exploration, Monica Meduri
Master's Projects
Diabetes is a lifelong illness that, if not detected or managed appropriately, turns into serious complications. Correct glucose forecasting is critical to ensuring timely interventions, thereby minimizing risks of hyperglycemia and hypoglycemia, and optimizing the management strategies of the disease. Classical machine learning models have been applied in the blood glucose forecasting problem for a long time, however, usage of transformer-based architectures is still scarce within the literature. Due to the self-attention mechanism, transformers can capture temporal relationships very effectively, which makes them suitable for time-series data. TFT is a novel framework proposed here to utilize time-series data from CGM …
Comparison Of Protein Structures Predicted By Genai Tools In A Zero-Shot Manner, Kruthi Shankar Rao
Comparison Of Protein Structures Predicted By Genai Tools In A Zero-Shot Manner, Kruthi Shankar Rao
Master's Projects
Generative AI models have vast applications and one such critical application explored in this study is protein structure prediction. The 3D structures of proteins determine their function. Our study mainly focuses on using generative AI models such as ESMFold and ColabFold to predict and examine naturally occurring and mutated sequences. The workflow begins with collecting antimicrobial resistance (AMR) and toxin-antitoxin (TA) protein data. The sequences are applied over pretrained AI models to predict protein structures. Following this, models are fine-tuned with original and mutated target datasets. A comparison of models’ performances is done using metrics such as root mean square …
Artifacts In Low-Pass Whole Genome Sequencing, Nguyen Mai Anh Do
Artifacts In Low-Pass Whole Genome Sequencing, Nguyen Mai Anh Do
Master's Projects
Low-pass whole genome sequencing (LP-WGS) provides a cost-effective way to achieve broad genomic coverage, but it comes with the challenge of sequencing artifacts that can complicate accurate variant detection. To address this, we developed a bioinformatics pipeline using Nextflow. Starting with raw sequencing data, the pipeline performed variant calling using VarDict, with Genome in a Bottle (GIAB) high-confidence variants serving as the benchmark for variant validation. We explored machine learning approaches, testing classifiers such as AdaBoost, ExtraTrees, and RandomForest, to evaluate variant classification. Twenty-two features generated by VarDict were fed into Machine Learning pipeline, with AdaBoost standing out for its …
Detecting Crustose Coralline Algae (Cca) In Marine Photos Using Mask R-Cnn, Vrushali Harshwardhan Deshpande
Detecting Crustose Coralline Algae (Cca) In Marine Photos Using Mask R-Cnn, Vrushali Harshwardhan Deshpande
Master's Projects
Coral reefs, made up of thousands of polyps - tiny sac-like marine invertebrates sea anemones and jellyfish, are important to marine ecosystems and prevent loss of life by acting as a natural barrier against storms, floods, and waves. These reefs support a wide range of species, many of which are underexplored and new species being discovered regularly. Crustose coralline algae (CCA) is one of the vital algal species that provides reef structure. Studying the abundance of CCA is important in helping marine biologists analyze coral reef health while understanding the impact of climate change on the marine lifeforms. This study …
An Ai-Based Conceptual Framework To Improve Program Management Of Complex Systems, Michael D. Parrish, Steven Corns
An Ai-Based Conceptual Framework To Improve Program Management Of Complex Systems, Michael D. Parrish, Steven Corns
Engineering Management and Systems Engineering Faculty Research & Creative Works
With evolving technologies, changing requirements, and limited budgets, governments and industries need to consider new methodologies to help streamline program lifecycle management, from cradle to grave, to ensure projects are delivered on time, on budget, and to the expected performance standards. Traditional approaches fail to adequately address the added complexities of System of Systems programs such as integration, interoperability, and variable lifecycle of subcomponents. The objective of this study is to assess and address the research question - can a new acquisition approach be designed to address and improve program lifecycle management of complex systems? A comparison study, using the …
Robust Phylogenetic Regression, Richard Adams, Zoe Cain, Raquel Assis, Michael Degiorgio
Robust Phylogenetic Regression, Richard Adams, Zoe Cain, Raquel Assis, Michael Degiorgio
Entomology and Plant Pathology Faculty Publications and Presentations
Modern comparative biology owes much to phylogenetic regression. At its conception, this technique sparked a revolution that armed biologists with phylogenetic comparative methods (PCMs) for disentangling evolutionary correlations from those arising from hierarchical phylogenetic relationships. Over the past few decades, the phylogenetic regression framework has become a paradigm of modern comparative biology that has been widely embraced as a remedy for shared ancestry. However, recent evidence has shown doubt over the efficacy of phylogenetic regression, and PCMs more generally, with the suggestion that many of these methods fail to provide an adequate defense against unreplicated evolution—the primary justification for using …
Optimized Gadolinium-Do3a Loading In Raft-Polymerized Copolymers For Superior Mr Imaging Of Aging Blood-Brain Barrier, Hunter A. Miller, Aaron Priester, Evan T. Curtis, Krista Hilmas, Ashleigh Abbott, Forrest M. Kievit, Anthony J. Convertine
Optimized Gadolinium-Do3a Loading In Raft-Polymerized Copolymers For Superior Mr Imaging Of Aging Blood-Brain Barrier, Hunter A. Miller, Aaron Priester, Evan T. Curtis, Krista Hilmas, Ashleigh Abbott, Forrest M. Kievit, Anthony J. Convertine
Materials Science and Engineering Faculty Research & Creative Works
The development of gadolinium-based contrast agents (GBCAs) has been pivotal in advancing magnetic resonance imaging (MRI), offering enhanced soft tissue contrast without ionizing radiation exposure. Despite their widespread clinical use, the need for improved GBCAs has led to innovations in ligand chemistry and polymer science. We report a novel approach using methacrylate-functionalized DO3A ligands to synthesize a series of copolymers through direct reversible addition-fragmentation chain transfer (RAFT) polymerization. This technique enables precise control over the gadolinium content within the polymers, circumventing the need for subsequent conjugation and purification steps, and facilitates the addition of other components such as targeting ligands. …
Effect Of Ph And Hydroxyapatite-Like Layer Formation On The Antibacterial Properties Of Borophosphate Bioactive Glass Incorporated Poly(Methyl Methacrylate) Bone Cement, Kara A. Hageman, Rebekah L. Blatt, William A. Kuenne, Richard K. Brow, Terence E. Mciff
Effect Of Ph And Hydroxyapatite-Like Layer Formation On The Antibacterial Properties Of Borophosphate Bioactive Glass Incorporated Poly(Methyl Methacrylate) Bone Cement, Kara A. Hageman, Rebekah L. Blatt, William A. Kuenne, Richard K. Brow, Terence E. Mciff
Materials Science and Engineering Faculty Research & Creative Works
Infection is a leading cause of total joint arthroplasty failure. Current preventative measures incorporate antibiotics into the poly (methyl methacrylate) (PMMA) bone cement that anchors the implant into the natural bone. With bacterial resistance to antibiotics on the rise, the development of alternative antibacterial materials is crucial to mitigate infection. Borate bioactive glass, 13–93-B3, has been studied previously for use in orthopedic applications due to its ability to be incorporated into bone cements and other scaffolds, convert into hydroxyapatite (HA)-like layer, and enhance the osseointegration and antibacterial properties of the material. The purpose of this study is to better understand …
Rcs-Slam: Range Of Communication Swarm Slam, Adam J. Hoburg
Rcs-Slam: Range Of Communication Swarm Slam, Adam J. Hoburg
Open Access Master's Theses
This work presents Range of Communication Swarm SLAM (RCS-SLAM) as a novel approach to simultaneous localization and mapping (SLAM) that is better suited for swarm robotic systems. RCS-SLAM introduces a novel SLAM front-end that leverages the effective range of an inter-robot communication medium to add inequality constraints between nodes in a pose graph whenever two robots communicate or relay communications. The centralized SLAM back-end then converts the inequality constrained pose graph into an unconstrained optimization problem using the penalty method to enforce the maximum possible range between communicating nodes. Converting to an unconstrained problem allows for the estimate to optimized …
New Associate Editors, S. Nicole Frey
New Associate Editors, S. Nicole Frey
Human–Wildlife Interactions
New associate editors include Breanna Martinico, Shannon Skalos, Paula Pebsworth, and Donna J. Perry.
Is Mitigation Translocation An Effective Method For Reducing Laysan Albatross–Military Aircraft Collisions?, Brian E. Washburn, Katherine D. Rubiano, William P. Bukoski
Is Mitigation Translocation An Effective Method For Reducing Laysan Albatross–Military Aircraft Collisions?, Brian E. Washburn, Katherine D. Rubiano, William P. Bukoski
Human–Wildlife Interactions
Wildlife–aircraft collisions (wildlife strikes) pose a serious risk to civil and military aircraft. Each year, Laysan albatrosses (Phoebastria immutabilis) attempt to establish a breeding colony on the airfield at the U.S. Navy’s Pacific Missile Range Facility (PMRF) located on the island of Kaua‘i, Hawai‘i, USA, resulting in a hazard to safe military aircraft operations at this facility. A long-term management program, with an emphasis on mitigation translocation (e.g., live-capture and translocation away from the area) of problematic individuals, has been conducted by the U.S. Department of Agriculture, Wildlife Services. However, the efficacy of mitigation translocation as a nonlethal …
Monograph Available: Toolkit To Address Free-Ranging Domestic Cats On Agency Lands Managed For Native Wildlife And Ecosystem Health
Human–Wildlife Interactions
This is an announcement about the published monograph titled "Toolkit to Address Free-ranging Domestic Cats on Agency Lands Managed for Native Wildlife and Ecosystem Health." This publication, part of the HWI Monograph Series, is online and open access.
The Invasive Species We Love And The Ones We Don't, S. Nicole Frey
The Invasive Species We Love And The Ones We Don't, S. Nicole Frey
Human–Wildlife Interactions
This is the letter from the editor-in-chief of Volume 18, Issue 1.
Efficacy Of A Laser As A Starling Deterrent And Its Effect On Lactating Dairy Cow Behavior, Callan A. Lichtenwalter, Marcos Marcondes, Kyle R. Taylor, Craig Mcconnel, Amber Adams Progar
Efficacy Of A Laser As A Starling Deterrent And Its Effect On Lactating Dairy Cow Behavior, Callan A. Lichtenwalter, Marcos Marcondes, Kyle R. Taylor, Craig Mcconnel, Amber Adams Progar
Human–Wildlife Interactions
European starlings (Sturnus vulgaris) cause damage (including structural damage) on dairies, eat cattle feed, and can potentially spread disease through their fecal matter. Deterring starlings from dairies without affecting cow (Bos taurus) welfare is vital, and lasers have been effective starling deterrence tools in urban roosts and in some crops. To evaluate if the use of lasers on dairies would affect starling use of freestall barns as night roosts, or lactating cow behavior, 1 laser was installed in each of the 2 freestall barns at the Knott Dairy Center at Washington State University, Pullman, Washington, USA. …
Impact Of Road Infrastructures On The Abundance Of Common Chameleon Populations, Pablo García-Quevedo, Francisco Díaz-Ruiz, Antonio Román Muñoz, Jesús Duarte, Adrián Martín-Taboada, José-María García-Carrasco, Miguel Ángel Farfán
Impact Of Road Infrastructures On The Abundance Of Common Chameleon Populations, Pablo García-Quevedo, Francisco Díaz-Ruiz, Antonio Román Muñoz, Jesús Duarte, Adrián Martín-Taboada, José-María García-Carrasco, Miguel Ángel Farfán
Human–Wildlife Interactions
The common chameleon (Chamaeleo chamaeleon) is a threatened species in Spain. The loss and transformation of their traditional habitats are among the main causes of its decline. Linear infrastructures, such as roads and highways, cause direct habitat loss, roadkill, and fragmentation of populations by acting as an artificial barrier. In this study, we investigated the potential effect of 2 high-speed road infrastructures in southern Spain on local populations of common chameleons. A total of 34 grids of 1x1 km were sampled, differentiating between grids without road presence (n = 17) and grids with road presence (n …
Snake Translocation Policies And Practices Within The United States, Robin E. Bedard, Megan Rottenborn, Emily Taylor
Snake Translocation Policies And Practices Within The United States, Robin E. Bedard, Megan Rottenborn, Emily Taylor
Human–Wildlife Interactions
Human–wildlife conflict with nuisance snakes (Serpentes) is rapidly increasing with human population growth and development rates. Translocation of nuisance snakes has become a widespread practice, aided by social media pages connecting people to volunteer and for-profit snake translocators. However, translocators often struggle to find information and resources from wildlife agencies about the policies required, and some may unintentionally use translocation procedures that disregard the health and survival of the snakes. The goals of this study were to (1) obtain data on policies, permitting, and training required for translocating nuisance snakes in each U.S. state that has snakes and (2) compare …
Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi
Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi
Mathematics and Statistics Faculty Research & Creative Works
Cluster Analysis Has Been Applied To A Wide Range Of Problems As An Exploratory Tool To Enhance Knowledge Discovery. Clustering Aids Disease Subtyping, I.e. Identifying Homogeneous Patient Subgroups, In Medical Data. Missing Data Is A Common Problem In Medical Research And Could Bias Clustering Results If Not Properly Handled. Yet, Multiple Imputation Has Been Under-Utilized To Address Missingness, When Clustering Medical Data. Its Limited Integration In Clustering Of Medical Data, Despite The Known Advantages And Benefits Of Multiple Imputation, Could Be Attributed To Many Factors. This Includes Methodological Complexity, Difficulties In Pooling Results To Obtain A Consensus Clustering, Uncertainty Regarding …
Segmented Fiber Optic Sensors Based On Hybrid Microwave-Photonic Interrogation, Wassana Naku, Osamah Alsalman, Jie Huang, Chen Zhu
Segmented Fiber Optic Sensors Based On Hybrid Microwave-Photonic Interrogation, Wassana Naku, Osamah Alsalman, Jie Huang, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, we propose and demonstrate a novel concept of segmented fiber optic sensors by integrating the fiber Bragg grating (FBG) reflector modality and a hybrid interrogation technique enabled by microwave photonics. As a proof of concept, a radiofrequency Fabry-Perot interferometer (FPI) based on an optical fiber with two FBGs as the two reflectors of the Fabry-Perot (FP) cavity is constructed. By measuring the frequency response of the FPI device followed by a joint-time-frequency-domain analysis, the interferogram of the FPI in the microwave domain and the time-domain signal of the FBGs can be unambiguously reconstructed. Thus, the two elements …
Enhanced Sensitivity And Robustness In An Embeddable Strain Sensor Using Microwave Resonators, Yan Tang, Yizheng Chen, Qi Zhang, Biyao Shi, Jie Huang
Enhanced Sensitivity And Robustness In An Embeddable Strain Sensor Using Microwave Resonators, Yan Tang, Yizheng Chen, Qi Zhang, Biyao Shi, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
This Paper Introduces A Novel, Cost-Effective, And Durable Strain Sensor With Exceptional Sensitivity And Resolution, Utilizing An Open-Ended Hollow Coaxial Cable Resonator (OE-HCCR). The OE-HCCR Is Characterized By Two Reflective Elements: A Metal Post That Connects The Inner And Outer Conductors At The Signal's Entrance, And A Terminal Flange Near The Coaxial Line's End, Establishing A Variable Gap. The Sensor Employs A Paired Anchor Ring In Conjunction With The Terminal Flange To Transduce And Direct Strain. Variations In The Gap Alter The Resonant Frequency By Modulating The Phase Of The Reflection Coefficient At The Cable's Terminus. Initial Calibration Revealed A …
Optical Fiber Sensors Based On Advanced Vernier Effect - A Review, Wassana Naku, Jie Huang, Chen Zhu
Optical Fiber Sensors Based On Advanced Vernier Effect - A Review, Wassana Naku, Jie Huang, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
The Optical Vernier Effect Has Emerged as a Powerful Tool for Enhancing the Sensitivity of Optical Fiber Interferometer-Based Sensors, Ushering in a New Era of Highly Sensitive Fiber Sensing Systems. While Previous Research Has Primarily Focused on the Physical Implementation of Vernier Effect-Based Sensors using Different Combinations of Interferometers, Conventional Vernier Sensors Face Several Challenges. These Include the Stringent Requirements on the Sensor Fabrication Accuracy to Achieve a Large Amplification Factor, the Necessity of using a Source with a Very Large Bandwidth and a Bulky Optical Spectrum Analyzer, and the Associated Complex Signal Demodulation Processes. This Article Delves into Recent …
Multimode Fiber-Based Interferometric Sensors With Microwave Photonics, Chen Zhu, Shuaifei Tian, Lingmei Ma, Jie Huang
Multimode Fiber-Based Interferometric Sensors With Microwave Photonics, Chen Zhu, Shuaifei Tian, Lingmei Ma, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Interferometry is one of the most widely used investigative techniques in various fields. With the implementation of interferometry on optical fibers, fiber optic interferometers (FOIs) have gained tremendous growth and advancement in the past four decades and have been explored for measurements of a diverse array of physical, chemical, and biological parameters. FOIs are typically constructed using single-mode fibers (SMFs) and are interrogated in the optical domain using probing light with a tightly controlled state of polarization (SOP), to ensure high-quality interference signals that facilitate sensing applications. The stringent requirement on the single-mode operation, as well as SOP, has hindered …
Electromagnetic-Circuital-Thermal-Mechanical Multiphysics Numerical Simulation Method For Microwave Circuits, Huan Huan Zhang, Zheng Lang Jia, Peng Fei Zhang, Ying Liu, Li Jun Jiang, Da Zhi Ding
Electromagnetic-Circuital-Thermal-Mechanical Multiphysics Numerical Simulation Method For Microwave Circuits, Huan Huan Zhang, Zheng Lang Jia, Peng Fei Zhang, Ying Liu, Li Jun Jiang, Da Zhi Ding
Electrical and Computer Engineering Faculty Research & Creative Works
An electromagnetic-circuital-thermal-mechanical Multiphysics numerical method is proposed for the simulation of microwave circuits. The discontinuous Galerkin time-domain (DGTD) method is adopted for electromagnetic simulation. The time-domain finite element method (FEM) is utilized for thermal simulation. The circuit equation is applied for circuit simulation. The mechanical simulation is also carried out by FEM method. A flexible and unified Multiphysics field coupling mechanism is constructed to cover various electromagnetic, circuital, thermal and mechanical Multiphysics coupling scenarios. Finally, three numerical examples emulating outer space environment, intense electromagnetic pulse (EMP) injection and high-power microwave (HPM) illumination are utilized to demonstrate the accuracy, efficiency, and …