Digital Commons Network^™

Underlying Substrate Effect On Electrochemical Activity For Hydrogen Evolution Reaction With Low-Platinum-Loaded Catalysts, Baleeswaraiah Muchharla, Peter V. Sushko, Kishor K. Sadasivuni, Wei Cao, Akash Tomar, Hani Elsayed-Ali, Adetayo Adedeji, Abdennaceur Karoui, Joshua M. Spurgeon, Bijandra Kumar

Electrical & Computer Engineering Faculty Publications

Platinum is known as the best catalyst for the hydrogen evolution reaction (HER) but the scarcity and high cost of Pt limit its widespread applicability. Herein, the role of the underlying substrate on the HER activity of dispersed Pt atoms is uncovered. A direct current magnetron sputtering technique is utilized to deposit transition metal (TM) thin films of W, Ti, and Ta as underlying substrates for extremely low loading of Pt (

Recent Progress In Microrna Detection Using Integrated Electric Fields And Optical Detection Methods, Logeeshan Velmanickam, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Low-cost, highly-sensitivity, and minimally invasive tests for the detection and monitoring of life-threatening diseases and disorders can reduce the worldwide disease burden. Despite a number of interdisciplinary research efforts, there are still challenges remaining to be addressed, so clinically significant amounts of relevant biomarkers in body fluids can be detected with low assay cost, high sensitivity, and speed at point-of-care settings. Although the conventional proteomic technologies have shown promise, their ability to detect all levels of disease progression from early to advanced stages is limited to a limited number of diseases. One potential avenue for early diagnosis is microRNA (miRNA). …

Different Visions From Biosview: A Brief Report, Lucas N. Potter, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

In this collaborative research endeavor at the intersection of biological safety and cybersecurity for BiosView labs, the authors highlight their engagement with a diverse student cohort. The chapter delves into the motivation behind collaborations extending beyond traditional academic research environments, emphasizing inclusivity. The meticulous examination of student demographics, including gender, self-reported ethnicity, and national origin, is detailed in the methodology. A student-centric approach is central to the exploration, focusing on aligning teaching and management styles with unique student needs. The chapter elaborates on effective teaching methodologies and management practices tailored for BiosView labs. A dedicated section emphasizes the purpose of …

Wavelet-Based Harmonization Of Local And Global Model Shifts In Federated Learning For Histopathological Images, W. Farzana, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Federated Learning (FL) is a promising machine learning approach for development of data-driven global model using collaborative local models across multiple local institutions. However, the heterogeneity of medical imaging data is one of the challenges within FL. This heterogeneity is caused by the variation in imaging scanner protocols across institutions, which may result in weight shift among local models leading to deterioration in predictive accuracy of global model. The prevailing approaches involve applying different FL averaging techniques to enhance the performance of the global model, ignoring the distinct imaging features of the local domain. In this work, we address both …

Adversarial Training Based Domain Adaptation Of Skin Cancer Images, Syed Qasim Gilani, Muhammad Umair, Maryam Naqvi, Oge Marques, Hee-Cheol Kim

Electrical & Computer Engineering Faculty Publications

Skin lesion datasets used in the research are highly imbalanced; Generative Adversarial Networks can generate synthetic skin lesion images to solve the class imbalance problem, but it can result in bias and domain shift. Domain shifts in skin lesion datasets can also occur if different instruments or imaging resolutions are used to capture skin lesion images. The deep learning models may not perform well in the presence of bias and domain shift in skin lesion datasets. This work presents a domain adaptation algorithm-based methodology for mitigating the effects of domain shift and bias in skin lesion datasets. Six experiments were …

Paper-Based Dna Biosensor For Rapid And Selective Detection Of Mir-21, Alexander Hunt, Sri Ramulu Torati, Gymama Slaughter

Electrical & Computer Engineering Faculty Publications

Cancer is the second leading cause of death globally, with 9.7 million fatalities in 2022. While routine screenings are vital for early detection, healthcare disparities persist, highlighting the need for equitable solutions. Recent advancements in cancer biomarker identification, particularly microRNAs (miRs), have improved early detection. MiR-21 is notably overexpressed in various cancers and can be a valuable diagnostic tool. Traditional detection methods, though accurate, are costly and complex, limiting their use in resource-limited settings. Paper-based electrochemical biosensors offer a promising alternative, providing cost-effective, sensitive, and rapid diagnostics suitable for point-of-care use. This study introduces an innovative electrochemical paper-based biosensor that …

Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

This paper aimed to evaluate the effects of different preparation parameters, including agitation speed, agitation time, and chilling temperature, on the structural and mechanical properties of a novel gelatin/elastin/sodium hyaluronate tissue engineering scaffold, recently developed by our research group. Fabricated using a combination of foaming and freeze-drying techniques, the scaffolds were assessed to understand how these parameters influence their morphology, internal microstructure, porosity, mechanical properties, and degradation behavior. The fabrication process used in this study involved preparing a homogeneous aqueous solution containing 8% gelatin, 2% elastin, and 0.5% sodium hyaluronate (w/v), which was then subjected to mechanical agitation at speeds …

A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment, Sergio Pallas Enguita, Chung-Hao Chen, Samuel Kovacic

Electrical & Computer Engineering Faculty Publications

This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.

Beyond Spatial Materiality, Towards Inter- And Intra-Subjectivity: Conceptualizing Exclusion In Education As Internalized Ableism And Psycho-Emotional Disablement, Anthony J. Maher, Justin A. Haegele

Human Movement Studies & Special Education Faculty Publications

Of the little written about educational exclusion, much of it considers exclusion as disabled students experiencing less access, opportunities and participation in education when compared to their nondisabled same-aged peers. Our article aims to move beyond these narrow, parochial, and reductive postulates by centering the inter- and intra-subjectivities of disabled students to conceptualize exclusion as experiences with internalized ableism and psycho-emotional disablement that may (or may not) be experienced in any or all material and social spaces in education. We cast light on ableism and psycho-emotional disablement in education so that we and others can challenge, disrupt, and transform it …

Complex Dynamics Of Coral Gene Expression Responses To Low Ph Across Species, Veronica Z. Radice, Ana Martinez, Adina Paytan, Donald C. Potts, Daniel J. Barshis

Biological Sciences Faculty Publications

Coral capacity to tolerate low pH affects coral community composition and, ultimately, reef ecosystem function. Low pH submarine discharges (‘Ojo’; Yucatán, México) represent a natural laboratory to study plasticity and acclimatization to low pH in relation to ocean acidification. A previous >2‐year coral transplant experiment to ambient and low pH common garden sites revealed differential survivorship across species and sites, providing a framework to compare mechanistic responses to differential pH exposures. Here, we examined gene expression responses of transplants of three species of reef‐building corals (Porites astreoides, Porites porites and Siderastrea siderea) and their algal endosymbiont communities …

Salmonella Detection In Food Using A Hek-Htlr5 Reported Cell-Based Sensor, Esma Eser, Victoria A. Felton, Rishi Drolia, Arun K. Bhunia

Biological Sciences Faculty Publications

The development of a rapid, sensitive, specific method for detecting foodborne pathogens is paramount for supplying safe food to enhance public health safety. Despite the significant improvement in pathogen detection methods, key issues are still associated with rapid methods, such as distinguishing living cells from dead, the pathogenic potential or health risk of the analyte at the time of consumption, the detection limit, and the sample-to-result. Mammalian cell-based assays analyze pathogens’ interaction with host cells and are responsive only to live pathogens or active toxins. In this study, a human embryonic kidney (HEK293) cell line expressing Toll-Like Receptor 5 (TLR-5) …

Receptor-Targeted Next-Generation Probiotics Ameliorate Mammalian Colitis, Nicholas L. F. Gallina, Vignesh Nathan, Akshay Krishnakumar, Dongqi Liu, Rishi Drolia, Nicole Irrizary Tardi, Yang Fu, Manalee Samadar, Shivendra Tenguria, Alvin Cai, Ruth Eunice Centeno-Martinez, Timothy A. Johnson, Abigail Cox, Lavanya Reddivari, Bruce Applegate, Xingjian Bai, Luping Xu, Deepti Tanjore, Ramesh Vemulapalli, Rahim Rahimi, Arun K. Bhunia

Biological Sciences Faculty Publications

Introduction: a loss of intestinal barrier function, inflammation, and an elevated expression of epithelial heat shock protein 60 (Hsp60) are features of an inflamed bowel. Probiotics have been used to alleviate colitis-induced pathologies, but offer poor adhesion and adaptation to the diseased gut. We hypothesize that enhancing probiotic adhesion in the inflamed bowel may ameliorate such pathologies. Listeria adhesion protein (LAP; 94-kDa acetaldehyde alcohol dehydrogenase) aids Listeria attachment to the epithelial cells by interacting with the mammalian receptor Hsp60. Bioengineered Lactobacillus casei probiotics (BLPs) expressing LAP showed strong interaction with epithelial Hsp60, a high immunomodulatory response, and sustained epithelial barrier …

Wild Sun Bears (Helarctos Malayanus) Exhibit Aseasonality In Parturition, Zachary A. David, Brian Crudge, Matt Hunt, Kirsty Officer, Vuthy Choun, Barbara Durrant, Megan A. Owen, Morokot Long, John P. Whiteman

Biological Sciences Faculty Publications

Seasonal reproduction can provide species with fitness advantages by allowing the birth of young to coincide with favorable environmental conditions, particularly in environments with high seasonal and intra-annual variation in these conditions. Seven of the eight species in the bear family (Ursidae) reproduce seasonally in both managed care and the wild; however, data for the eighth species, the sun bear (Helarctos malayanus), is unclear. Sun bears have been observed to reproduce throughout the year in managed care, yet currently there are no clear data of birth timing for wild sun bear cubs. Here we investigate the seasonality of …

Half Of Atlantic Reef-Building Corals At Elevated Risk Of Extinction Due To Climate Change And Other Threats, Luis Gutierrez, Beth Polidoro, David Obura, Francoise Cabada-Blanco, Christi Linardich, Emma Pettersson, Paul Pearce-Kelly, Krista Kemppinen, Juan Jose Alvarado, Lorenzo Alvarez-Filip, Anastazia Banaszak, Pilar Casado De Amezua, James Crabbe, Aldo Croquer, Joshua Feingold, Elizabeth Goergen, Stefano Goffredo, Bert Hoeksema, Danwei Huang, Emma Kennedy, Diego Kersting, Marcelo Kitahara, Petar Kružić, Margaret Miller, Flavia Nunes, Juan Pablo Quimbayo, Andrea Rivera-Sosa, Rosa Rodríguez-Martínez, Nadia Santodomingo, Michael Sweet, Mark Vermeij, Estrella Villamizar, Greta Aeby, Khatija Alliji, Daniel Bayley, Elena Couce, Benjamin Cowburn, C. Isabel Nuñez Lendo, Sean Porter, Kaveh Samimi-Namin, Tom Shlesinger, Bryan Wilson

Biological Sciences Faculty Publications

Atlantic reef-building corals and coral reefs continue to experience extensive decline due to increased stressors related to climate change, disease, pollution, and numerous anthropogenic threats. To understand the impact of ocean warming and reef loss on the estimated extinction risk of shallow water Atlantic reef-building scleractinians and milleporids, all 85 valid species were reassessed under the IUCN Red List Categories and Criteria, updating the previous Red List assessment of Atlantic corals published in 2008. For the present assessment, individual species declines were estimated based on the modeled coral cover loss (1989–2019) and projected onset of annual severe bleaching events (2020–2050) …

Ai And Ml-Based Risk Assessment Of Chemicals: Predicting Carcinogenic Risk From Chemical-Induced Genomic Instability, Ajay Vikram Singh, Preeti Bhardwaj, Peter Laux, Prachi Pradeep, Madleen Busse, Andreas Luch, Akihiko Hirose, Christopher J. Osgood, Michael W. Stacey

Biological Sciences Faculty Publications

Chemical risk assessment plays a pivotal role in safeguarding public health and environmental safety by evaluating the potential hazards and risks associated with chemical exposures. In recent years, the convergence of artificial intelligence (AI), machine learning (ML), and omics technologies has revolutionized the field of chemical risk assessment, offering new insights into toxicity mechanisms, predictive modeling, and risk management strategies. This perspective review explores the synergistic potential of AI/ML and omics in deciphering clastogen-induced genomic instability for carcinogenic risk prediction. We provide an overview of key findings, challenges, and opportunities in integrating AI/ML and omics technologies for chemical risk assessment, …

Exploring Angiotensin Ii And Oxidative Stress In Radiation-Induced Cataract Formation: Potential For Therapeutic Intervention, Vidya P. Kumar, Yali Kong, Riana Dolland, Sandra R. Brown, Kan Wang, Damian Dolland, David Mu, Milton L. Brown

Department of Biomedical and Translational Sciences Faculty Publications

Radiation-induced cataracts (RICs) represent a significant public health challenge, particularly impacting individuals exposed to ionizing radiation (IR) through medical treatments, occupational settings, and environmental factors. Effective therapeutic strategies require a deep understanding of the mechanisms underlying RIC formation (RICF). This study investigates the roles of angiotensin II (Ang II) and oxidative stress in RIC development, with a focus on their combined effects on lens transparency and cellular function. Key mechanisms include the generation of reactive oxygen species (ROS) and oxidative damage to lens proteins and lipids, as well as the impact of Ang II on inflammatory responses and cellular apoptosis. …

Can Large Language Models Discern Evidence For Scientific Hypotheses? Case Studies In The Social Sciences, Sai Koneru, Jian Wu, Sarah Rajtmajer

Computer Science Faculty Publications

Hypothesis formulation and testing are central to empirical research. A strong hypothesis is a best guess based on existing evidence and informed by a comprehensive view of relevant literature. However, with exponential increase in the number of scientific articles published annually, manual aggregation and synthesis of evidence related to a given hypothesis is a challenge. Our work explores the ability of current large language models (LLMs) to discern evidence in support or refute of specific hypotheses based on the text of scientific abstracts. We share a novel dataset for the task of scientific hypothesis evidencing using community-driven annotations of studies …

Identifying New Cancer Genes Based On The Integration Of Annotated Gene Sets Via Hypergraph Neural Networks, Chao Deng, Hong-Dong Li, Li-Shen Zhang, Yiwei Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation

Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited.

Results

Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of …

Hite: A Fast And Accurate Dynamic Boundary Adjustment Approach For Full-Length Transposable Element Detection And Annotation, Kang Hu, Peng Ning, Minghua Xu, You Zou, Jianye Chang, Xin Gao, Yaohang Li, Jue Ruan, Bin Hu, Jianxin Wang

Computer Science Faculty Publications

Recent advancements in genome assembly have greatly improved the prospects for comprehensive annotation of Transposable Elements (TEs). However, existing methods for TE annotation using genome assemblies suffer from limited accuracy and robustness, requiring extensive manual editing. In addition, the currently available gold-standard TE databases are not comprehensive, even for extensively studied species, highlighting the critical need for an automated TE detection method to supplement existing repositories. In this study, we introduce HiTE, a fast and accurate dynamic boundary adjustment approach designed to detect full-length TEs. The experimental results demonstrate that HiTE outperforms RepeatModeler2, the state-of-the-art tool, across various species. Furthermore, …

The Combined Focal Loss And Dice Loss Function Improves The Segmentation Of Beta-Sheets In Medium-Resolution Cryo-Electron-Microscopy Density Maps, Yongcheng Mu, Thu Nguyen, Bryan Hawickhorst, Willy Wriggers, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Although multiple neural networks have been proposed for detecting secondary structures from medium-resolution (5–10 Å) cryo-electron microscopy (cryo-EM) maps, the loss functions used in the existing deep learning networks are primarily based on cross-entropy loss, which is known to be sensitive to class imbalances. To monitor and tune the performance of various loss functions for the secondary structure detection problem, we investigated five loss functions: cross-entropy, Focal loss, Dice loss, and two combined loss functions. Using a U-Net architecture in our DeepSSETracer method and a dataset composed of 1,355 box-cropped atomic-structure/density-map pairs, we found that a newly designed loss function …

Flexible Fitting Of Alphafold2-Predicted Models To Cryo-Em Density Maps Using Elastic Network Models: A Methodological Affirmation, Maytha Alshammari, Jing He, Willy Wriggers

Computer Science Faculty Publications

Motivation: This study investigates the flexible refinement of AlphaFold2 models against corresponding cryo-electron microscopy (cryo-EM) maps using normal modes derived from elastic network models (ENMs) as basis functions for displacement. AlphaFold2 generally predicts highly accurate structures, but 18 of the 137 models of isolated chains exhibit a TM-score below 0.80. We achieved a significant improvement in four of these deviating structures and used them to systematically optimize the parameters of the ENM motion model.

Results: We successfully refined four AlphaFold2 models with notable discrepancies: lipid-preserved respiratory supercomplex (TM-score increased from 0.52 to 0.69), flagellar L-ring protein (TM-score increased from 0.53 …

Sccad: Cluster Decomposition-Based Anomaly Detection For Rare Cell Identification In Single-Cell Expression Data, Yunpei Xu, Shaokai Wang, Qilong Feng, Jiazhi Xia, Yaohang Li, Hong-Dong Li, Jianxin Wang

Computer Science Faculty Publications

Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate …

Retrogressive Document Manipulation Of Us Federal Environmental Websites, Lesley Frew, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

Changes made to webpages can affect their retrievability. Often this is done with the intention of increasing the page's search engine ranking to improve overall access to information on the page. The Environmental Data and Governance Initiative (EDGI) created a dataset that describes changes on US federal environmental webpages between 2016 and 2020. EDGI noted that many environmental terms were deleted from the pages, but without user data, claims that page retrievability and public information access were lowered are only anecdotal. The Open Resource for Click Analysis in Search (ORCAS) dataset was created during the same time frame, from 2017 …

Identifying Patterns For Neurological Disabilities By Integrating Discrete Wavelet Transform And Visualization, Soo Yeon Ji, Sampath Jayarathna, Anne M. Perrotti, Katrina Kardiasmenos, Dong Hyun Jeong

Computer Science Faculty Publications

Neurological disabilities cause diverse health and mental challenges, impacting quality of life and imposing financial burdens on both the individuals diagnosed with these conditions and their caregivers. Abnormal brain activity, stemming from malfunctions in the human nervous system, characterizes neurological disorders. Therefore, the early identification of these abnormalities is crucial for devising suitable treatments and interventions aimed at promoting and sustaining quality of life. Electroencephalogram (EEG), a non-invasive method for monitoring brain activity, is frequently employed to detect abnormal brain activity in neurological and mental disorders. This study introduces an approach that extends the understanding and identification of neurological disabilities …

Triphlapan: Predicting Hla Molecules Binding Peptides Based On Triple Coding Matrix And Transfer Learning, Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li

Computer Science Faculty Publications

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding …

757transfamily: Empowering Parents To Raise Their Transgender Child Through Knowledge, Connection, And Joy, Jessica Gurley

Institute for the Humanities Master's Papers, Projects, and Capstones

Parents of transgender and non-binary children often want to support their children, but are not sure how. Giving these parents the support and resources they need will increase their ability to support their children, further increasing the chance that their children will live a long, healthy, authentic life.

I built a website, and organized a workshop that parents can attend in order to access information and resources about the transgender community. These parents will receive the support they need to be better equipped to support their gender-diverse children. I will be collecting information about the parents' feelings and experience towards …

Rising Threat - Deepfakes And National Security In The Age Of Digital Deception, Dougo Kone-Sow

Cybersecurity Undergraduate Research Showcase

This paper delves into the intricate landscape of deepfakes, exploring their genesis, capabilities, and far-reaching implications. The rise of deepfake technology presents an unprecedented threat to American national security, propagating disinformation and manipulation across various media formats. Notably, deepfakes have evolved from a historical backdrop of disinformation campaigns, merging with the advancements of artificial intelligence (AI) and machine learning to craft convincing but false multimedia content.

Examining the capabilities of deepfakes reveals their potential for misuse, evidenced by instances targeting individuals, companies, and even influencing political events like the 2020 U.S. elections. The paper highlights the direct threats posed by …

A Review Of Threat Vectors To Dna Sequencing Pipelines, Tyler Rector

Cybersecurity Undergraduate Research Showcase

Bioinformatics is a steadily growing field that focuses on the intersection of biology with computer science. Tools and techniques developed within this field are quickly becoming fixtures in genomics, forensics, epidemiology, and bioengineering. The development and analysis of DNA sequencing and synthesis have enabled this significant rise in demand for bioinformatic tools. Notwithstanding, these bioinformatic tools have developed in a research context free of significant cybersecurity threats. With the significant growth of the field and the commercialization of genetic information, this is no longer the case. This paper examines the bioinformatic landscape through reviewing the biological and cybersecurity threats within …

"I Think There Is A Place For Small Programs:" Advocating, Implementing, And Sustaining Tpc Programs In Small Us Institutions, Martha Lynn Russell

English Theses & Dissertations

Technical and Professional Communication (TPC) programs in small institutions compose of over a third of all programs in the US, yet this space has been understudied by most scholars. To fill this gap, this dissertation presents findings from one-hour interviews with twenty-six TPC program directors in small US institutions with undergraduate populations of less than six thousand. The results of this dissertation include the ways that small institutions are advocating, implementing, and sustaining their TPC program in unique ways with implications for how any TPC programs regardless of size can learn from these findings.

A New View Of Chlorophyll Dynamics In The Southern Mid-Atlantic Bight From A Two-Year High-Resolution Spray Glider Survey, Francesco Lane

OES Theses and Dissertations

The southern Mid-Atlantic Bight (MAB) near Cape Hatteras, NC, USA, is likely a hotspot for the episodic export of carbon-rich shelf waters to the open ocean. Over a 2 year period, from March 2017 to May 2019, Spray gliders repeatedly occupied transects, along the slope and across the shelf, generating high-resolution chlorophyll fluorescence (fChl) data in the southern MAB. This study implements an fChl calibration method utilizing remotely sensing ocean color as a standard. We validate the method’s utility by demonstrating a reduction in post-calibration cross-mission fChl variability and demonstrating close correspondence between the calibrated fChl data and an in …