Digital Commons Network^™

Explainable Neural Networks With Guarantees: A Sparse Estimation Approach, Antoine Ledent, Peng Liu

Research Collection School Of Computing and Information Systems

Balancing predictive power and interpretability has long been a challenging research area, particularly in powerful yet complex models like neural networks, where nonlinearity obstructs direct interpretation. This paper introduces a novel approach to constructing an explainable neural network that harmonizes predictiveness and explainability. Our model is designed as a linear combination of a sparse set of jointly learned features, each derived from a different trainable function applied to a single 1-dimensional input feature. Leveraging the ability to learn arbitrarily complex relationships, our neural network architecture enables automatic selection of a sparse set of important features, with the final prediction being …

Dr. Tongue: Sign-Oriented Multi-Label Detection For Remote Tongue Diagnosis, Yiliang Chen, Steven S. C. Ho, Cheng Xu, Yao Jie Xie, Wing Fai Yeung, Shengfeng He, Jing Qin

Research Collection School Of Computing and Information Systems

Tongue diagnosis is a vital tool in Western and Traditional Chinese Medicine, providing key insights into a patient's health by analyzing tongue attributes. The COVID-19 pandemic has heightened the need for accurate remote medical assessments, emphasizing the importance of precise tongue attribute recognition via telehealth. To address this, we propose a Sign-Oriented multi-label Attributes Detection framework. Our approach begins with an adaptive tongue feature extraction module that standardizes tongue images and mitigates environmental factors. This is followed by a Sign-oriented Network (SignNet) that identifies specific tongue attributes, emulating the diagnostic process of experienced practitioners and enabling comprehensive health evaluations. To …

On Explicit Solutions For Coupled Reaction-Diffusion And Burgers-Type Equations With Variable Coefficients Through A Riccati System, Jose M. Escorcia, Erwin Suazo

School of Mathematical & Statistical Sciences Faculty Publications

This work is concerned with the study of explicit solutions for generalized coupled reaction-diffusion and Burgers-type systems with variable coefficients. Including nonlinear models with variable coefficients such as the diffusive Lotka-Volterra model, the Gray-Scott model, the Burgers equations. The equations' integrability (via the explicit formulation of the solutions) is accomplished by using similarity transformations and requiring that the coefficients fulfill a Riccati system. We present traveling wave-type solutions as well as solutions with more complex dynamics and relevant features such as bending. A Mathematica file has been prepared as supplementary material, verifying the Riccati systems used in the construction of …

Pathways To Chronic Disease Detection And Prediction: Mapping The Potential Of Machine Learning To The Pathophysiological Processes While Navigating Ethical Challenges, Ebenezer Afrifa-Yamoah, Eric Adua, Emmanuel Peprah-Yamoah, Enoch O. Anto, Victor Opoku-Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi

Research outputs 2022 to 2026

Chronic diseases such as heart disease, cancer, and diabetes are leading drivers of mortality worldwide, underscoring the need for improved efforts around early detection and prediction. The pathophysiology and management of chronic diseases have benefitted from emerging fields in molecular biology like genomics, transcriptomics, proteomics, glycomics, and lipidomics. The complex biomarker and mechanistic data from these “omics” studies present analytical and interpretive challenges, especially for traditional statistical methods. Machine learning (ML) techniques offer considerable promise in unlocking new pathways for data-driven chronic disease risk assessment and prognosis. This review provides a comprehensive overview of state-of-the-art applications of ML algorithms for …

Quantum Control And Simulation Using Hamiltonian Engineering In Solid-State Nmr, Linta Joseph

Dartmouth College Ph.D Dissertations

Lattices of dipolar coupled nuclear spins in natural crystals are large, interacting quantum systems -- ideal platforms to simulate non-equilibrium many-body dynamics. Using the magnetic resonance toolkit, which includes Dynamic Nuclear Polarization (DNP), Hamiltonian engineering, and multiple-quantum Nuclear Magnetic Resonance (NMR) experiments, we study aspects of coherent control, manipulation, and readout of the complex dynamics of the spin system in NMR quantum simulation.

First, applying Hamiltonian engineering sequences, we control the system evolution. Specifically, we use a combination of numerical simulations and NMR experiments on adamantane to evaluate and compare the performance of several known sequences that aim to suppress …

Treating Ground Water For Agricultural And Individual Consumption, Gabby Miller, Bronson Scott, Michael Clawson

Biomedical Engineering

This project, conducted in collaboration with Cal Poly seniors and Da Vinci High School students, aims to develop a solar-powered groundwater purification system. This system is designed to provide clean water for agricultural use and individual consumption, addressing the growing concerns of groundwater contamination and accessibility needs. The final prototype integrates a gravity filtration system combined with chemical purification, utilizing aluminum sulfate and chlorine to remove particulates, bacteria, and organic compounds.

The research phase involved an extensive review of groundwater contamination issues, existing filtration technologies, and market analysis. Key design constraints included cost-effectiveness, ease of maintenance, and minimal energy consumption, …

Experimental Approaches To Investigate Biophysical Interactions Between Homeodomain Transcription Factors And Dna, Fadwa Mekkaoui, Robert A. Drewell, Jacqueline M. Dresch, Donald E. Spratt

Chemistry

Homeodomain transcription factors (TFs) bind to specific DNA sequences to regulate the expression of target genes. Structural work has provided insight into molecular identities and aided in unraveling structural features of these TFs. However, the detailed affinity and specificity by which these TFs bind to DNA sequences is still largely unknown. Qualitative methods, such as DNA footprinting, Electrophoretic Mobility Shift Assays (EMSAs), Systematic Evolution of Ligands by Exponential Enrichment (SELEX), Bacterial One Hybrid (B1H) systems, Surface Plasmon Resonance (SPR), and Protein Binding Microarrays (PBMs) have been widely used to investigate the biochemical characteristics of TF-DNA binding events. In addition to …

A System Dynamics Model For Predicting African Armyworm Occurrence And Population Dynamics, Bonoukpoè Mawuko Sokame, Brian Kipkorir, Komi Mensah Agboka, Saliou Niassy, Yeneneh Belayneh, Maged Elkahky, Henri E.Z. Tonnang

All Peer-Reviewed Publications

This study develops a comprehensive system dynamics model to predict and manage African armyworm (Spodoptera exempta) outbreaks, a major threat to cereal crops across Africa. We applied system dynamics approache with its archetypes (causal loop diagram (CLD), reinforcing (R) and balancing (B)) to analyse the population dynamics of the pest. The VENSIM modelling platform (Ventana Systems Inc., DSS 8.2) was used to implement the models and carry out the simulations. The research integrates extensive data from 1980 to 2023, encompassing the African armyworm's life cycle stages, climatic variables, and intervention strategies, to simulate potential outbreak scenarios and evaluate the impacts …

Biophysical Response Of A Coastal Woodland To Extreme Water Deficit During A Year Of Record-Breaking Heat, Caitlin E. Moore, Sally E. Thompson, Jason Beringer, Wesley Cooper, Simone Gelsinari, Hoang Long Nguyen, Huanhuan Wang, Qiaoyun Xie, Richard P. Silberstein

Research outputs 2022 to 2026

Global terrestrial and ocean surface temperatures continue to reach record levels, resulting in heat waves, drought, and prolonged heat stress experienced by vegetation in many regions. In 2023-2024, coastal terrestrial ecosystems in Western Australia were particularly affected, experiencing their driest and hottest summer since observations began in the early 1900s. Banksia woodlands are a threatened ecological community in this region that are endangered by the cumulative impacts of climate change, clearing and changing groundwater regimes, the last of which is strongly influenced by the dual use of groundwater resources by the ecosystem and by the ∼2 million people in the …

Interactive Mapping Of Allergenic Urban Street Trees In Australia, Diman Krwanji, Anna J. Hopkins, Kristina Lemson, M. Hanson

Research outputs 2022 to 2026

Tree pollen can be a persistent allergen for sensitised individuals, causing allergic rhinitis and asthmatic symptoms. Increased urbanisation results in larger populations living in cities and relying on urban greenspaces for recreation and associated ecosystem services, where the street landscapes are determined by urban planners. Urban forest strategies broadly divide planting choices based on biological functionality, climate resilience and environmental benefits but increasingly the associated physical and mental health impacts of urban vegetation are being considered. Here, we studied pollen allergenicity in four Australian cities by incorporating measures of allergenicity in existing street tree asset databases and visualising these using …

Patient Consent And The Right To Notice And Explanation Of Ai Systems Used In Health Care, Meghan E Hurley, Benjamin H Lang, Kristin Marie Kostick-Quenet, Jared N Smith, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

Given the need for enforceable guardrails for artificial intelligence (AI) that protect the public and allow for innovation, the U.S. Government recently issued a Blueprint for an AI Bill of Rights which outlines five principles of safe AI design, use, and implementation. One in particular, the right to notice and explanation, requires accurately informing the public about the use of AI that impacts them in ways that are easy to understand. Yet, in the healthcare setting, it is unclear what goal the right to notice and explanation serves, and the moral importance of patient-level disclosure. We propose three normative functions …

Explainable Neural Networks With Guarantee: A Sparse Estimation Approach, Antoine Ledent, Peng Liu

Research Collection School Of Computing and Information Systems

Balancing predictive power and interpretability has long been a challenging research area, particularly in powerful yet complex models like neural networks, where nonlinearity obstructs direct interpretation. This paper introduces a novel approach to constructing an explainable neural network that harmonizes predictiveness and explainability. Our model is designed as a linear combination of a sparse set of jointly learned features, each derived from a different trainable function applied to a single 1-dimensional input feature. Leveraging the ability to learn arbitrarily complex relationships, our neural network architecture enables automatic selection of a sparse set of important features, with the final prediction being …

Graph Foundation Models: Concepts, Opportunities And Challenges, Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Fang Yuan, Lichao Sun, Philip S. Yu, Chuan Shi

Research Collection School Of Computing and Information Systems

Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains. Meanwhile, the field of graph machine learning is witnessing a paradigm transition from shallow methods to more sophisticated deep learning approaches. The capabilities of foundation models in generalization and adaptation motivate graph machine learning researchers to discuss the potential of developing a new graph learning paradigm. This paradigm envisions models that are pre-trained on extensive graph data and can be adapted for various graph tasks. Despite this burgeoning interest, there is a noticeable lack …

Too Much Of A Good Thing: Lessons From Compromised Rootworm Bt Maize In The Us Corn Belt, Ziwei Ye, Christina Difonzo, David A. Hennessy, Jinhua Zhao, Felicia Wu, Shawn P. Conley, Aaron J. Gassmann, Erin W. Hodgson, Bryan Jensen, Janet J. Knodel, Bradley Mcmanus, Lance J. Meinke, Andrew Michel, Bruce Potter, Nicholas J. Seiter, Jocelyn L. Smith, Joseph L. Spencer, Kelley J. Tilmon, Robert J. Wright, Christian H. Krupke

Department of Entomology: Faculty Publications

Widespread use of genetically engineered maize targeting the corn rootworm complex (Diabrotica species) has raised concerns about insect resistance. Twelve years of university field trial and farm survey data from ten United States Corn Belt states indicate that maize hybrids expressing toxins derived from the bacterium Bacillus thuringiensis (Bt maize) exhibited declining protection from rootworm feeding with increased planting while pest pressures simultaneously decreased. The analysis revealed a tendency to overplant Bt maize, leading to substantial economic losses; this was particularly striking in eastern Corn Belt states. Our findings highlight the need to go beyond the “tragedy of the …

Executive Functioning, Diabetes Distress, And Diabetes Management Among Adolescents With Type 1 Diabetes: Youth And Parent Perspectives, Allison Choe, Emily M. Fredericks, Dana L. Albright, Joyce M. Lee, Julie M. Sturza, Hurley O. Riley, Niko Kaciroti, Katherine W. Bauer, Allison L. Miller

Health Services and Informatics Research

Objective: Most adolescents with Type 1 Diabetes (T1D) do not achieve recommended glycemic targets, placing them at risk for long-term complications. Executive functioning (EF), or the cognitive processes that support goal-directed action and management of behavior, emotion, and cognition, is proposed to support effective T1D management and contribute to glycemic stability. We sought to examine associations of EF with T1D management behaviors and diabetes-related distress in adolescents with T1D.

Methods: Participants were 13–17-year-olds (M = 15.44, SD = 1.38 years) from a randomized controlled trial (N = 88). We conducted secondary analyses of preintervention data. Youth and their …

2025 Final Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Quality Assurance Project Plan (Qapp) For Microbial Analysis And Biotreatability Study, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

2025 Final Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Quality Assurance Project Plan (Qapp) For Microbial Analysis And Biotreatability Study, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Seeing The Light: Optics Research At Bethel, Nathan Lindquist

Day of Scholarship

The department of Physics and Engineering has a strong tradition of research, projects, coursework, and labs in optics. Optical sciences is a broad and interdisciplinary field that covers imaging, fiber optic communications, lasers, and sensing, with applications in biology, chemistry, medicine, engineering, and many more. This presents some of the research that has happened over the past few years, including research presented by students at national conferences.

The Effects Of Imidacloprid And Polyester Microfibers On The Larval Development Of The Endangered Sunflower Star, Alexandra G. Tissot, Elise F. Granek, Fiona Curliss, Augustin Kalytiak-Davis, Jason Hodin, Michelle L. Hladik

Environmental Science and Management Faculty Publications and Presentations

Sea star wasting syndrome has affected numerous species of sea star, with populations of Pycnopodia helianthoides (Brandt, 1835) left most at risk. As their populations are struggling to recover, it is important to gain a better understanding of the impacts that the multiple stressors in their habitats can have on their populations. Contaminant stressors in particular are of increasing importance, because aquatic organisms can be exposed to a dynamic range of contaminants from nearby anthropogenic activity that may affect their future recovery efforts. This study is the first to quantify the effects of contaminant stressors on the larvae of P. …

Human-Ai Collaboration In Writing: A Multidimensional Framework For Creative And Intellectual Authorship, James Hutson

Faculty Scholarship

The integration of AI technologies into the writing process has significantly altered traditional notions of authorship, creativity, and intellectual labor. Historically, writing was seen as a human-driven cognitive and creative exercise, but with the rise of generative AI tools such as ChatGPT and Claude, the line between human and AI contributions has become increasingly ambiguous. This paper addresses the limitations of the current sliding scale model, which views AI involvement as ranging from “none” to “complete”. In its place, we propose a new multidimensional framework that more accurately reflects the complexity of human-AI collaboration in writing. The model includes axes …

Exploration Of Differential Equation Models For Phage-Bacteria Population Dynamics, John Lawrence Palacios, Rebecca A. Segal

Spora: A Journal of Biomathematics

Bacteriophages are viruses that infect and replicate within bacteria. Lytic phages cause the bacterial cell to burst, killing the bacteria. These types of phages can be used to treat patients with antibiotic-resistant bacterial infections. As a step in developing successful treatment protocols, we aim to understand the population dynamics of phages and bacteria using an in vitro model. We model the dynamics using the Campbell model, which consist of a delay differential equation (DDE), as a base model. We extended the model by including the emergence of phage resistance. We then compared the DDE model with a parallel ordinary differential …

A Review Of Racial Differences And Disparities In Ecg, Jianwei Zheng, Chizobam Ani, Islam Abudayyeh, Yunfan Zheng, Cyril Rakovski, Ehsan Yaghmaei, Omolola Ogunyemi

Mathematics, Physics, and Computer Science Faculty Articles and Research

The electrocardiogram (ECG) is a widely used, non-invasive tool for diagnosing a range of cardiovascular conditions, including arrhythmia and heart disease-related structural changes. Despite its critical role in clinical care, racial and ethnic differences in ECG readings are often underexplored or inadequately addressed in research. Variations in key ECG parameters, such as PR interval, QRS duration, QT interval, and T-wave morphology, have been noted across different racial groups. However, the limited research in this area has hindered the development of diagnostic criteria that account for these differences, potentially contributing to healthcare disparities, as ECG interpretation algorithms largely developed from major …

Variation In Thermal Tolerance Plasticity And The Costs Of Heat Exposure In The Estuarine Sea Hare, Phyllaplysia Taylori, Richelle L. Tanner, Rauri C. K. Bowie, Cynthia Y. Wang-Claypool, Jonathan H. Stillman

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate change is increasing average temperatures and the frequency and intensity of thermal extremes in coastal marine environments. Organisms in coastal marine habitats are accustomed to environmental fluctuations and possess physiological plasticity that may be advantageous in response to increased occurrence of extremes. To examine whether such plasticity is locally adapted to environmental conditions, we investigated the relationship between genetic diversity and thermal tolerance plasticity in 11 populations of the direct-developing intertidal sea hare, Phyllaplysia taylori, on the western coast of the United States. Using whole-organism metrics of muscle function and metabolic rate and a ddRADseq genomic approach, we …

Bloom: Behavioral Learning And Outcome Observation In Microbes, Sean Sarwar Haque, Luke Compton Wharton, Ming Lin, Razvan Voicu

Symposium of Student Scholars

Understanding how pathogens respond to physical changes in their environment is crucial for developing effective treatments and preventative measures. Current research often relies on static models or experimental data that either fail to capture the dynamic interactions within cellular environments or are not generalizable to other types of pathogens. This project aims to address this gap by creating a comprehensive cell simulation that models pathogens and their response to chemical, physical, and physiological changes. The proposed solution is a simulation that integrates biological data and computational modeling to replicate the behavior of pathogens in real time as they are affected …

A Novel Preprocessing Model For Multi Modal Brain Mri Image Classification For Stroke Prognosis, Alwin Joseph, Chandra J

Northeast Journal of Complex Systems (NEJCS)

Magnetic Resonance Imaging (MRI) is an imaging technique used for the diagnosis and observing the progression in various neurological disorders. Stroke is one of the prominent neurological disorders that creates significant impacts in the patients. It occurs when the blood supply to part of the brain is interrupted or reduced, preventing brain tissues from getting oxygen and nutrients. Multimodal data from various modalities help clinicians in proper prognosis of stroke. Ischemic Stroke Lesion Segmentation Challenge (ISLES22) provides data of stroke data for various stroke patients, the dataset consists of three modalities of data – Fluid Attenuated Inversion Recovery (FLAIR), Apparent …

Reviews And Syntheses: Variable Inundation Across Earth’S Terrestrial Ecosystems, James Stegen, Amy J. Burgin, Michelle H. Busch, Joshua B. Fisher, Joshua Ladau, Jenna Abrahamson, Lauren Kinsman-Costello, Li Li, Xingyuan Chen, Thibault Datry, Nate Mcdowell, Corianne Tatariw, Anna Braswell, Jillian M. Deines, Julia A. Guimond, Peter Regier, Kenton Rod, Edward K. P. Bam, Etienne Fluet-Chouinard, Inke Forbrich, Kristin L. Jaeger, Teri O’Meara, Tim Scheibe, Erin Seybold, Jon N. Sweetman, Jianqiu Zheng, Daniel C. Allen, Elizabeth Herndon, Beth A. Middleton, Scott Painter, Kevin Roche, Julianne Scamardo, Ross Vander Vorste, Kristin Boye, Ellen Wohl, Margaret Zimmer, Kelly Hondula, Maggi Laan, Anna Marshall, Kaizad F. Patel

Watershed Sciences Faculty Publications

The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal …

Stabilization Of Argan Oil Nanoemulsions Using Chitosan Extracted From Pink Shrimp Shells, Yousra Mdarhri, Ikram Bouziane, Ilyace Korodowou, Narjisse Mokhtari, Lama Rissouli, Fakhita Touhami, Mohamed Chabbi, Ahmed Touhami

Physics & Astronomy Faculty Publications

This study investigates the use of chitosan, extracted from pink shrimp shells, as a stabilizer for argan oil nanoemulsions. Chitosan was obtained through demineralization, deproteination, bleaching, deacetylation, and purification, then characterized through potentiometric titration, viscometry, X-ray diffraction (XRD), scanning electron microscopy (SEM), and purity assessments. The resulting chitosan was used to stabilize nanoemulsions formulated with extra-virgin argan oil and a nonionic surfactant using the phase inversion composition (PIC) method. The stability of the nanoemulsion was assessed through light scattering, zeta potential, viscosity, and pH measurements. The extracted chitosan exhibited high purity, a deacetylation degree of 88.34%, a molecular weight of …

Reviews And Syntheses: Variable Inundation Across Earth’S Terrestrial Ecosystems, James Stegen, Amy J. Burgin, Michelle H. Busch, Joshua B. Fisher, Joshua Ladau, Jenna Abrahamson, Lauren Kinsman-Costello, Li Li, Xingyuan Chen, Thibault Datry, Nate Mcdowell, Corianne Tatariw, Anna Braswell, Jillian M. Deines, Julia A. Guimond, Peter Regler, Kenton Rod, Edward K. P. Bam, Etienne Fluet-Chouinard, Inke Forbrich, Kristin L. Jaeger, Teri O'Meara, Tim Scheibe, Erin Seybold, Jon N. Sweetman, Jianqiu Zheng, Daniel C. Allen, Elizabeth Herndon, Beth A. Middleton, Scott Painter, Kevin Roche, Julianne Scamardo, Ross Vander Vorste, Kristin Boye, Ellen Wohl, Margaret Zimmer, Kelly Hondula, Maggi Laan, Anna Marshall, Kaizad F. Patel

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal …

Urbanization Impacts Dissolved Organic Matter Concentration And Quality In A Southeastern United States Watershed, Gwendolyn M. Hopper, Erik M. Smith, Jade Dormoy-Boulanger, Claudia R. Benitez-Nelson

Faculty Publications

Blackwater rivers are named due to their exceptionally high concentrations of chromophoric dissolved organic matter (CDOM). They are the predominant lotic ecosystem in the United States Southeastern Coastal Plain, a region experiencing some of the nation’s highest rates of development. This study assessed variability in DOM concentration and composition across forested to urbanized blackwater systems in coastal South Carolina, U.S. Dissolved organic carbon and nutrient concentrations as well as absorbance and fluorescence optical properties reveal that urban sites have lower concentrations, elemental ratios, and less complex DOM. In contrast, forested blackwater sites have concentrations an order of magnitude higher, elevated …

Evaluation Of Physical And Chemical Condition Of A Group Of Waterloggedarchaeological Woods From The Yenikapı 16 Shipwreck, Sedef Hetto, Namik Kiliç, Asli Gökçe Kiliç

Turkish Journal of Earth Sciences

This study examined the physical and chemical condition of waterlogged archaeological wood (WAW) samples from the Yenikapı 16 shipwreck of plane (Platanus L.), elm (Ulmus L.), pine (Pinus L.), and fir (Abies L.), representing species with different wood properties. The maximum water content (MWC) and basic density (BD) values of 74 WAW samples from the shipwreck were calculated, and 7 of 74 samples were selected for analysis using scanning electron microscopy (SEM), X-ray fluorescence (XRF), and Fourier transform infrared spectroscopy (FTIR). The availability of samples, appropriate size, the species of the wood, and the wood’s degradation were all considered. The …