Digital Commons Network^™

Supplemental Bibliographic Details. From 2001 Mars Odyssey To Earth’S Climate Crisis: Integrating Gamma Spectroscopy, Martian Soil Simulants, And Plant Genomes For Agroecology, Anchored In Sri Lanka’S Mars-Context Serpentinites, Suniti Karunatillake, Maheshi Dassanayake, Carlos Gary Bicas

Planetary Science Lab

Bibliographic details follow to supplement hyperlinked citations in the multinational GANGOTRI-supporting project conceived by Karunatillake, Dassanayake, and Gary-Bicas

Creating A University-Based Accessible Makerspace For Use By Local Community Members Through Participatory Design Workshops, Erin Higgins, John J. Magee Iv, Foad Hamidi

Computer Science

While Do-It-Yourself Assistive Technology (DIY-AT) has been shown to provide needed AT for individuals who might not otherwise have access, the makerspaces utilized to create these technologies have proven to be inaccessible. A promising direction for creating accessible makerspaces is to utilize participatory methods to develop new spaces for use by a diverse community of individuals. We explored these possibilities through participatory design workshops focused on building a new accessible community makerspace situated within a university campus setting. Through these workshops, we found that there are unique physical, technical, and human supports needed to create an accessible space for the …

Advances And Challenges In Digitally Connected Point-Of-Care Biosensing, Abdellatif Ait Lahcen, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Point-of-care (POC) biosensors are undergoing a paradigm shift from isolated diagnostic tools to digitally connected, intelligent platforms that enable continuous and decentralized healthcare delivery. This review critically examines recent advances in wearable, implantable, and portable biosensors, highlighting how integration with wireless communication, the Internet of Medical Things (IoMT), and artificial intelligence is transforming their functionality and clinical utility. Particular attention is given to innovations such as smartphone-enabled interfaces, cloud-based analytics, and machine learning-assisted analysis, which collectively enhance sensitivity, specificity, and user accessibility across diverse healthcare settings, from personalized home monitoring and bedside diagnostics to deployment in resource-limited regions. The review …

Essays On Accelerated Failure Time Models For Recurrent Event Data, Emmanuel Masavo Djegou

Doctoral Dissertations

Recurrent event data arise in many fields such as medicine, reliability, insurance, and economics, where the same event may occur repeatedly for a subject. Accelerated Failure Time (AFT) models provide an intuitive framework for relating covariates to event times and offer a useful alternative to proportional hazards models, allowing direct prediction of event timing under right censoring. However, existing AFT extensions for recurrent events, such as accelerated gap time (AGT) models, often fail to account for interventions between events and may not capture complex temporal patterns.

In this work, we first propose a class of semiparametric AGT models incorporating an …

Flexible Membrane Electrodes For Use In High-Capacity Lithium-Ion Batteries, David A. Denemark

College of Graduate Studies: Theses & Dissertations

Wearable electronic devices require high-capacity flexible batteries to improve user comfort and increase usage time per charge. In this thesis, flexible lithium-ion battery (LIB) electrodes are prepared using a novel and scalable phase inversion method, embedding one-dimensional SnO₂ nanowires and double-walled carbon nanotubes within a porous polyacrylonitrile asymmetric membrane. The optimized electrode delivered an initial specific discharge capacity of 915.93 mAh g⁻¹, approximately 2.5 times greater than conventional graphite anodes, with 61.99% capacity retention after 45 cycles. The incorporation of a carbon mesh substrate further enhanced both electrochemical and mechanical performance, achieving 89.46% capacity retention after 45 cycles and a …

Evaluating The Role Of Power Electronics In Enhancing Renewable Energy And Smart Grid Performance: A Review, Muhammad Irfan Habib

ASEAN Journal on Science and Technology for Development

The review article demonstrates the importance of power electronics in propelling the increase of renewables and increasing the efficiency of contemporary electrical grids. In particular, it highlights the need for bidirectional converters for effective energy management in vehicle-to-grid (V2G) systems with two-way power transfer. The paper examines the series of complications offered by the significantly large integration of power electronic converter-interfaced renewables, such as those related to system steadiness, power quality, and resignation bottlenecks. Also, it recognizes a mix of new technologies, such as wide bandgap (WBG) semiconductors like silicon carbide (SiC) and gallium nitride (GaN), that deliver superior performance …

Design Of An Economic Order Quantity–Based Dashboard For Vaccine Packaging Inventory Management, Hadi Susanto, Susmitha Canny, Alexandra Elizabeth Callistha, Shakira Dwi Purwandari, Naila Davina Aurelia

ASEAN Journal on Science and Technology for Development

Background: Timely availability of vaccine packaging is critical to pharmaceutical supply chain reliability, as packaging materials play a key role in maintaining cold chain integrity during distribution. Inadequate availability of packaging materials can disrupt vaccine delivery even when finished vaccines are ready for shipment. The case company faces frequent delivery delays, insufficient safety stock, and irregular replenishment of vaccine packaging materials, which have jeopardized the organization’s target of achieving a 90% on-time delivery rate.

Objective: To design and evaluate an Economic Order Quantity (EOQ)–based inventory dashboard for vaccine packaging that standardizes ordering decisions and strengthens stock visibility in pharmaceutical distribution …

Guidelines For Standard Basic Notations In Applied Statistics, Abhaya Indrayan, Shivani Saini Ms

COBRA Preprint Series

Whereas some statistical notations are standard and uniformly used by different workers, many are not. Varying notations lead to confusion among the readers, particularly those engaged with applied statistics material, such as medical professionals. This communication proposes that all basic notations be standardized so that the same notations are consistently used by different authors, in different books, journals, and articles for the benefit of those who are not rigorously trained statisticians. Guidelines for such standard notations are also provided. The lead must be taken by statisticians.

Investigating The Role Of Humic Acid In The Adsorption Mechanics Of Acetaminophen On Potassium Persulfate-Aged Polyethylene Terephthalate (Pet), Andrew Littleton, Maria Danielle Garrett, Phd

SPARK Symposium Presentations

Pharmaceutical contaminants such as acetaminophen (APAP) are showing a rising presence in aquatic environments, where their interactions with microplastics (MPs) can potentially modulate natural degradation mechanisms. Concurrent presence of the two substances has been shown to potentiate increase their individual harmful effects. This study investigates whether oxidative aging and humic-acid surface modification of PET microplastics influence APAP adsorption.

In this study, UV-aging was reproduced using an iron (II)-activated potassium persulfate (Fe(II)-KPS) oxidation system. Aqueous dissolved organic matter (DOM) is simulated using multi-hour exposure to humic acid. The MPs are then removed from the solution to examine adsorption mechanisms. While most …

First Record Of Arrhenophagus Chionaspidis Aurivillius (Hymenoptera: Encyrtidae) Parasitizing White Mango Scale In Kenya: Its Potential Distribution And Prospects In Biocontrol, Francis Obala, Abdelmutalab G.A. Azrag, Rehemah Gwokyalya, Shepard Ndlela, Ingo Grass, Georg Petschenka, Sunday Ekesi, Samira A. Mohamed

All Peer-Reviewed Publications

The white mango scale, Aulacaspis tubercularis Newstead (Hemiptera: Diaspididae), is one of the most destructive pests of mango worldwide. Its current management in most of the invaded areas largely depends on the intensive use of chemical insecticides. Biological control using parasitoids represents one of the most effective and environmentally sustainable management options. However, in Kenya, one of Africa's leading mango-producing countries, no effective parasitoid species associated with A. tubercularis had previously been recorded. This study aimed to identify encyrtid parasitoids associated with A. tubercularis in Kenya, and to assess how bioclimatic factors influence their occurrence and habitat suitability. Mango leaves …

Thermal Requirements And Phenology Modelling Of A Drosophila Suzukii Population: Implications For Pest Risk Under A Changing Climate, Shepard Ndlela, Abdelmutalab G.A. Azrag, Esther Owino Awuor, Ibrahim Maholidy Farid, Samira Abuelgasim Mohamed

All Peer-Reviewed Publications

Drosophila suzukii (spotted-wing drosophila) is an invasive pest causing significant economic losses in soft-skinned fruit crops globally. This study presents comprehensive temperature-dependent life table data and phenology models for an African D. suzukii population collected in Kenya. Developmental time, mortality, fecundity, and adult longevity were assessed under constant temperatures from 12 to 30 °C. Using Insect Life Cycle Modelling (ILCYM) software, linear and nonlinear models were applied to characterise the effects of temperature on life history traits. Additionally, spatial risk indices including Establishment Risk Index (ERI), Generation Index (GI), and Activity Index (AI) were mapped globally for current and future …

Algorithmic Trading In Idiosyncratic-Payoff Markets: A Multi-Agent System For On-Chain Prediction Contracts, Saif Aldeen A.K. Agha

CMC Senior Theses

This thesis documents the design, deployment, and forward-test evaluation of an evolutionary multi-agent algorithmic trading system on Polymarket, the largest decentralized prediction market. The system pairs a locally-hosted 72-billion-parameter language model with a gradient-boosted statistical filter and an evolutionary selection mechanism that maintains a population of approximately 500 autonomous trading agents. Each agent generates a probability estimate for an event, compares it to the prevailing market price, and trades the resulting disagreement.

The central empirical exercise estimates a panel regression of trade-level profit on the absolute disagreement between the agent's probability estimate and the market price, controlling for agent identity, …

Motivation System Evoked By High Performance Work System In Chinese Universities And Colleges - An Examination Of The Relationship Between Human Resource Practices, Basic Psychological Needs, And Job Performance, Juan Chen

Doctoral

High Performance Work Systems (HPWS) are strategic, integrated Human Resource Practices (HRPS) designed to enhance employee abilities, motivation, and opportunities for participation, driving sustained organisational performance. While early research emphasized commitment HRPS, recent studies recognise that control and commitment HRPS are complementary rather than mutually exclusive, with neither holding an absolute advantage. Their success depends on contextual factors such as country, industry,organisation, economic environment, and workforce. In Chinese higher education institutions, transitioning from a high-commitment “iron rice bowl” system to a more control-oriented HR model has created tensions between efficiency and academic freedom. Based on the resource-based view, social exchange …

Bridging The Knowledge-Practice Gap In Breast Cancer Awareness: A Nationwide Online Cross-Sectional Kap Study Among Adult Females In Nigeria, Madinat Hassan, Taofeek Tope Adegboyega, Bilkisu Usman Farouk, Sunday Zeal Bala, Rachael Olufunmilayo Oduyemi, Kazeem Owolabi, Munir Sani, Miracle Uwa Livinus, Hannatu Usman Ayuba, Sadiq Hassan, Ifeyinwa Maureen Okeke, Abednego Shekari, Murtala Jibril

Chemistry & Biochemistry Faculty Publications

Background and Aims

Breast cancer (BCa) is a major cause of cancer morbidity and mortality among women in Nigeria, with late presentation contributing to poor outcomes. This study assessed knowledge, attitudes, and willingness to perform breast self-examination (BSE) among adult females in Nigeria and examined associated factors.

Methods

We conducted a descriptive cross-sectional online survey between February 16 and April 30, 2024. A structured, pretested questionnaire was disseminated through digital platforms, yielding 711 consenting adult female respondents from all six geopolitical zones. Knowledge, attitude, and willingness-to-perform-BSE measures were analyzed using descriptive statistics, linear regression, and binary logistic regression. Associations were …

Training Set Augmentation And Biology-Aware Harmonization Improve Radiomic Models For Lung Cancer Prediction In Indeterminate Nodules, Claire Huchthausen, Menglin Shi, Gabriel De Sousa, James Larner, Einsley Janowski, Jonathan Colen, Krishni Wijesooriya

Data Science Faculty Publications

CT radiomics-based machine learning has potential to predict lung cancer in pulmonary nodules (PNs) earlier than standard-of-care methods. Low malignancy rates in early-development PNs and variable image acquisition hinder development of radiomic models for diagnosing these PNs. To address these challenges, we augmented training using later-development PNs and harmonized for acquisition effects. We examine early-development benign and malignant PNs (n = 106) below the sensitivity of standard-of-care diagnosis. Classifiers predicting malignancy performed near chance when trained on ComBat-harmonized radiomic features from only early-development PNs. We then augmented training with later-development benign and malignant PNs (n = 225). We evaluated whether …

When Climate Change Forces Flight: Legal Duties In The Age Of Retreat, Mark P. Nevitt

Faculty Articles

In the face of climate-driven disasters, government officials and individuals alike must decide whether to invest in climate-exposed areas or retreat. This Article analyzes emerging legal and policy issues associated with both climate retreat (when the government relocates people and infrastructure away from climate-exposed areas) and abandonment (when individuals leave climate-exposed areas, following natural disasters or otherwise). I argue that government-driven climate retreat must consider four overlapping legal duties, raising novel questions in an era of climate destabilization. First, does the government have an affirmative duty to rescue its citizens, and is this duty transformed by the government’s role in …

Radial And Carotid Arterial Pulse Signals For Assessing Cardiovascular Function At Rest And During Post-Exercise Recovery In A Heart Transplant Patient: A Case Study, Md Mahfuzur Rahman, Mamun Hasan, Jennifer F. May, John M. Herre, Leryn Reynolds, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Aim: This study investigates the feasibility of using radial and carotid arterial pulse signals to assess cardiovascular (CV) function at rest and during post-exercise recovery in a heart transplant (HTx) patient. Method: Two micro-fabricated tactile sensors were used to simultaneously acquire arterial pulse signals at the radial artery (RA) and carotid artery (CA). Measurements were taken at rest and at multiple time points post-exercise on three subjects: an HTx patient, a percutaneous coronary intervention (PCI; coronary stent) patient and a healthy control. An SDOF-TF-based time-frequency analysis algorithm was applied to extract a comprehensive set of CV parameters, including heart rate …

Dynamic Modeling Of The Earth's Trapped Proton Environment, Xiaojing Xu, Steve R. Blattnig, Francis F. Badavi, Martha S. Clowdsley, Edward J. Semones

Physics Faculty Publications

Context: Reliable prediction of space radiation exposure is critical for safeguarding spacecraft systems and ensuring astronaut health during missions. Accurate radiation risk assessment for space mission requires advanced models of the Earth’s trapped proton environment. These models must reflect temporal variations driven by geomagnetic field evolution and solar cycle modulation. Existing static models, such as AP8 and IRENE-AP9, are not designed to fully capture these evolving conditions. Aims: This paper presents a dynamic modeling method for the prediction of trapped proton fluxes, which incorporate time-dependent variations due to geomagnetic field evolution and solar cycle fluctuations. Methods: The …

Real-Space Imaging Of The Electron-Pair Density Hole In Molecular Auger-Meitner Decay, Mats Simmermacher, Nathan Goff, Andres Moreno Carrascosa, Elke Fasshauer, Thomas Northey, Lingyu Ma, Haiwang Yong, Brian Stankus, Asami Odate, Xuan Xu, Wenping Du, Kyle Acheson, Joseph C. Cooper, Daniel Ratner, Mengning Liang, Ruaridh Forbes, Michael P. Minitti, Adam Kirrander, Peter M. Weber

Physics Faculty Publications

Electrons in matter can rearrange extremely quickly under external perturbations, underpinning subsequent structural and chemical transformations. Coulomb interactions between neighbouring electrons often shape this response, giving rise to correlated motion and strongly affecting the distribution of electrons in the system. Here we show that non-resonant hard X-ray scattering can directly access changes in the radial electron-pair density during the rapid rearrangement of core and valence electrons. We do this by studying sulfur hexafluoride molecules undergoing Auger–Meitner decay. We exploit a second-order interaction between the X-ray photons and the molecules to trigger and probe the decay dynamics with a single pulse, …

End-To-End Modeling For The Ross Sea Region Marine Protected Area: A Review Of Available Tools For Conservation Objectives, James R. Lovvorn, Cara Nissen, Alexis A. Bahl, Erik Behrens, Cassandra M. Brooks, Katy Christensen, Michael S. Dinniman, Lilian A. Dove, Alice K. Duvivier, Eileen E. Hofmann, Hayley Kwasniewski, Young Shin Kwon, Sharon E. Stammerjohn, Lei Xing

CCPO Publications

The challenge of protecting marine ecosystems, including biodiversity and manifold interactions in changing environments, has encouraged development of end-to-end models linking physical drivers through entire food webs to upper-level predators. Ideally such models should have temporal and spatial resolution adequate to capture important small-scale processes, while including scales large enough to encompass local food webs and movements of wide-ranging consumers. The need for component submodels to be manipulated and upgraded independently by scientists from different disciplines, and used selectively depending on questions addressed, favors modular structure allowing linkage of different submodels with varying strengths and weaknesses. As an example, this …

Artificial Intelligence And Consumer Well-Being: A Cross Domain Systemic Review, Setar Lytle, Mahesh Gopinath

Marketing Faculty Publications

Artificial intelligence (AI) is increasingly embedded in everyday consumption, yet evidence on its longer-term implications for consumer eudaimonic well-being remains dispersed across disciplines and application contexts. This review integrates that literature to clarify the domains, theoretical explanations, and conditions through which AI shapes consumer well-being. Following PRISMA and SPAR-4-SLR procedures, we reviewed research published from January 2010 to January 2026. From 6058 records, 480 studies across psychology, business, and human-technology interaction met the inclusion criteria. The evidence is organised through psychological, social, and technological perspectives and identifies six interconnected domains: mental health, cognitive development, physical health, personal growth, autonomy and …

A Comparative Evaluation Of Data Imbalance Handling Techniques In Machine Learning Models For One-Year Mortality Prediction In Liver Cirrhosis, Sumiya Hasan Trisha

UNF Graduate Theses and Dissertations

Liver cirrhosis is associated with substantial morbidity and mortality, making one-year mortality prediction a clinically relevant problem. Using a liver cirrhosis dataset as the motivating application, this thesis evaluates five machine learning classifiers—Logistic Regression, Random Forest, XGBoost, LightGBM, and CatBoost—under five class-imbalance handling strategies: Baseline learning, Random Oversampling, SMOTE-NC, ADASYN, and Cost-Sensitive Learning. Hyperparameter tuning was conducted using randomized search, and predictive performance was assessed over 200 iterations of Monte Carlo Cross-Validation using Accuracy, Precision, Recall, Fl-score, and ROC-AUC.

The results suggest that imbalance-handling strategies can materially affect predictive performance, particularly recall. Because the outcome of interest is death within …

Integrative Approaches And Data Analysis For Single-Cell Rna Sequencing Data, Teng Long

Computer Science and Engineering Dissertations

The rapid growth of single-cell RNA sequencing and transcriptomic datasets has created major computational challenges in causal discovery, representation learning, and biologically faithful data generation. To address these challenges, this dissertation presents three complementary deep learning frameworks for the analysis and modeling of transcriptomic data. Together, these methods form an integrative computational toolkit for understanding complex biological systems from high-dimensional and heterogeneous gene expression data.

First, this dissertation introduces DAG-VAERL, a causal discovery framework that integrates variational autoencoders, graph neural networks, reinforcement learning, and attention mechanisms to infer directed acyclic graphs for gene regulatory network analysis. DAG-VAERL improves causal structure …

Data-Driven Climate Damage Functions For Capital Formation: Estimating The Climate Penalty Using Maching Learning, Pramudya Wicaksono

All Graduate Theses, Dissertations, and Other Capstone Projects

Traditional integrated assessment models assume parametric climate damage functions that may miss nonlinearities, heterogeneity, and dynamic effects on investment. This thesis develops a data-driven climate damage function for capital formation by estimating the predictive relationship between climate conditions and future gross fixed capital formation (% GDP) across 125 countries over 1982–2019. We construct a panel dataset by combining daily ERA5 climate reanalysis data (accessed via the Copernicus Climate Data Store API and aggregated to yearly country-level variables including temperature anomalies, extreme heat days, frost days, precipitation, and solar radiation) with economic indicators from the World Bank World Development Indicators and …

Absolute Quantification And Identification Of Rna From Rna-Lipid Nanoparticles Using High Resolution Mass Spectrometry, Jason C. Funderburk, Yasir A. Alshehry, Matthew S. Halquist Phd, Sandro R.P. Da Rocha Phd

Graduate Research Posters

Background

RNA therapeutics are a rising drug category with potential use for a range of conditions encompassing infectious diseases to therapies for cancer, diseases, and genetic disorders. RNA-lipid nanoparticles (RNA-LNPs) are the prominent delivery method for these therapeutics approved products include mRNA vaccines and polyneuropathy treatments. The emergency use authorizations and orphan drug status of current RNA-LNP drugs has allowed approval without finalization of the regulatory analytical procedures for quality monitoring. The objective of the study was to develop an LC-MS assay to simultaneously measure identity and concentration of two therapeutically relevant intact RNA constructs extracted from RNA-LNPs to enhance …

Simulating Social Attitudes With Llms: Accuracy, Demographic Effects, And Refusal Behavior In The Sensitive Domain Of Suicide Prevention, Cristina J. Perez, Michael P. Vasquez Jr., Philippe J. Giabbanelli, Patrick Y. Wu

VMASC Publications

Large language models (LLMs) are increasingly used to simulate public opinion, yet their validity in sensitive policy domains remains underexplored. We evaluate whether LLMs can reproduce attitudes toward suicide prevention policies using 32 questions drawn from seven nationally representative U.S. surveys (2023-2025). We systematically vary demographic conditioning (race/ethnicity, gender, age, education, income, party), prompt framing (direct elicitation, respondent embodiment, specialist embodiment), and model architecture (GPT-5 Nano, DeepSeek V3.2, Meta Llama 3.1 8B, Mistral Small 24B). Across 811,560 prompts, the mean absolute error—the average gap between predicted and human response distributions—is 23 percentage points. We also find that LLM responses to …

An Exploration Of Geomagnetically Induced Currents And The Accessibility Of Geomagnetic Data Collection, Richard Le

Physics Theses

Geomagnetically Induced Currents (GICs) are electrical currents induced in long grounded conductors during geomagnetic disturbances. They represent one of the primary space weather hazards to critical infrastructure, particularly high-voltage power transmission systems and other grounded conductor networks such as pipelines. As modern society becomes more dependent on these systems, understanding and mitigating the impacts of space weather has become increasingly important. This thesis examines the physical mechanisms that generate GICs, from the interaction of the solar wind with Earth’s Magnetosphere to Magnetosphere-Ionosphere-Thermosphere (MIT) coupling and the current systems that drive geomagnetic disturbances (GMDs). Case studies from Zimbabwe and Finland illustrate …

An Llm-Driven System For Doctor-Patient Simulation, Akilan Amithasagaran

Computer Science Theses

Effective physician-patient communication is fundamental to clinical competence, yet traditional simulation-based training methods using standardized patients and high-fidelity manikins are costly, resource-intensive, and difficult to scale. This dissertation presents CLiVR (Conversational Learning system in Virtual Reality), an LLM-driven system that integrates large language models and 3D avatars to simulate doctor-patient interactions for medical communication training.

CLiVR addresses three key limitations in existing virtual reality medical training platforms. First, the system operates on standalone Meta Quest 3 hardware with realistic 3D patient avatars featuring synchronized lip movements and speech-based interaction. Second, CLiVR grounds LLM responses using a curated syndrome-symptom database, constraining …

An Ensemble Classifier For Ordinal Outcomes In High-Dimensional Genomics Data, Heranga K. Rathnasekara, Sinjini Sikdar

Mathematics & Statistics Faculty Publications

Analysis of genomics data for predicting disease outcomes is a fast-growing field in medical research. There often exist categorical, specifically, ordinal outcomes that need to be predicted based on genomic profiles. This has led to recent development of some high-dimensional ordinal classification methods that can address the large dimensionality of the genomic covariate set. These high-dimensional ordinal models tend to vary widely in their performance depending on the data they are applied to and the evaluation criteria used. In this article, we outline an ensemble ordinal classifier that integrates different ordinal modeling approaches through bootstrap-based model evaluation, multi-metric performance assessment, …

Characterization Of Phytoplankton-Excreted Metabolites Mediating Carbon Flux Through The Surface Ocean, Yuting Zhu, Hanna S. Anderson, Eli Salcedo, Samuel E. Miller, Krista Longnecker, Melissa C. Kido Soule, Sheean T. Haley, Gretchen J. Swarr, Rogier Braakman, Sonya T. Dyhrman, Elizabeth B. Kujawinski

Chemistry & Biochemistry Faculty Publications

The marine labile dissolved organic carbon (DOC) pool is a dynamic reservoir of thousands of molecules that cycles approximately one-quarter of Earth’s primary production within days to weeks. After excretion by phytoplankton and other microbes, metabolites are rapidly consumed, resulting in low standing concentrations (picomolar to low nanomolar). Despite the decades-long search for labile DOC sources and molecular identities, marine phytoplankton exometabolomes are not well characterized, largely due to difficulties in measuring small polar molecules in saline water. Here, we profiled the exometabolomes of six axenic phytoplankton species representing key functional groups including a diatom (Thalassiosira pseudonana CCMP1335), a …