Digital Commons Network^™

Aquatic Macrophytes As Nature-Based Solutions: Challenges And Opportunities Across Inland And Coastal Waters, Morgan Botrel, Roxane Maranger, Lindsay L. Trottier, Mathieu Cusson, Lars L. Iverson, Fanny Noisette, Christian Nozais, Katrine Turgeon, Andrea Bertolo, Thibaud André-Alphonse, Simon Bélanger, Arthur De Grandpré, Jean-Olivier Goyette, Sabine Hilt, Ladd Johnson, Valérie Langlois, Martin Laporte, Félix Lauzon, Brigitte Légaré, Anne Ola, Marie-Pomme Presne-Poissant, Matthieu Prugne, Caroline Susini, Richard Zimmerman

OES Faculty Publications

Macrophytes are foundation species whose use as nature-based solution (NbS) in aquatic ecosystems can help reduce climate change impacts while mitigating biodiversity loss. The discrepancy in research and application of macrophytes as NbS across inland and marine coastal ecosystems is an opportunity to expand the concept and learn from different approaches. We report on an initiative uniting marine and freshwater scientists that compared knowledge on macrophytes as NbS across realms, identified advances and gaps in their use, and synthesized challenges and opportunities for application. We conducted a bibliometric analysis and an expert participatory exercise around recent review papers. We reveal …

Regional Oceanographic Controls On Water Column Nitrogen Fixation In Northern Australian Waters, Douglas G. Capone, Ajit Subramaniam, Yubin Raut, Joseph P. Montoya, Margaret R. Mulholland, Rachel Ann Foster, Miles Furnas, Edward J. Carpenter

OES Faculty Publications

Large blooms of the diazotrophic cyanobacteria, Trichodesmium, have been re-ported along the north coast of Australia and are readily evident in remote sensing images. During a research cruise in November 1999, we sampled from Townsville to Broome, examined Trichodesmium population densities and their rates of carbon and N₂ fixation alongside microscopy-based cell counts of them and other cyanobacte-rial diazotrophs. Additionally, we also enumerated the picophytoplankton community using flow-cytometry, measured bulk chlorophyll concentrations, carbon and N₂ fixation rates, and water column hydrography, enabling comparison of diazotrophic and picophytoplankton functional groups across the system. Agglomerative hierarchical clustering analysis of physicochemical oceanographic …

Microplastics Suppress Copepod Grazing Of The Harmful Algal Bloom-Forming Dinoflagellate, Alexandrium Catenella, Megan Ladds, Christopher Gobler

OES Faculty Publications

While harmful algal blooms (HABs) are prominent occurrences in coastal zones where microplastic concentrations are maximal, the manner in which microplastics may influence food webs and HABs is poorly understood. This study explored how polystyrene microplastics affected copepod grazing of the saxitoxin-synthesizing harmful dinoflagellate, Alexandrium catenella, as well as a non-toxic dinoflagellate, Gymnodinium aureolum. Experiments were performed using multiple densities of microplastics (250 – 10,000 mL^–¹) of differing sizes (4 and 10 µm), as well as multiple densities of microalgae in microplates. The addition of 10 µm microplastics at densities of 1000 – 10,000 beads mL^{– …}

Tick Lipocalin Triggers Mammalian Igfbp-3-Mediated Apoptosis In Macrophages And Keratinocytes, Krittika Nandy, P. P. Mahesh, Lichao Liu, Daniel E. Sonenshine, Hameeda Sultana, Girish Neelakanta

Biological Sciences Faculty Publications

Ticks secrete several molecules, including lipocalins, in their saliva during blood feeding on a vertebrate host. In this study, we provide novel evidence on the role of Ornithodoros turicata americanus tick lipocalin (Otlip) in modulating cytokine expression and in triggering apoptosis in mammalian macrophages and keratinocytes. The cytokine array analysis revealed significantly increased secretion of insulin-like growth factor-binding protein 3 (IGFBP3) from murine macrophage cell line upon treatment with recombinant Otlip protein (rGST-Otlip) when compared to the secretion noted from cells treated with a control protein (rGST). Similar observation with cytokine protein array analysis was noted when murine macrophages were …

Microarray Analysis Of Human Abdominal Aortic Aneurysm With Emphasis On Cardiovascular Genes Revealed Differentially Expressed Genes, Song Lu, Li Ping Li, John V. White, Xiaoying Zhang, Ifeyinwa Nwaneshiudu, Adaobi Nwaneshiudu, Nectaria Ntaoula, John Gaughan, Dimitri S. Monos, Wan-Lu Lin, Charalambos C. Solomides, Emilia L. Oleszak, Chris D. Platsoucas

Biological Sciences Faculty Publications

Background/Aim: We examined gene expression profiles in abdominal aortic aneurysm (AAA) lesions vs. normal aortas by cDNA microarray and real-time quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR).

Materials and Methods: Phosphorus (32P)-labeled cDNA from AAA specimens (mean AAA size 6.65 cm) and normal aortas were hybridized with a 588-gene microarray primarily of the cardiovascular system. The results were validated by qRT-PCR.

Results: A total of 35 out of the 588 genes were differentially expressed, with either log2 ratio of AAAs/controls ≥1 (upregulated; 20 genes) or ≤−1 (downregulated; 15 genes) in AAA lesions vs. normal aorta, and 25 of these were significantly …

Evaluating Species At Risk In Data-Limited Fisheries: A Productivity-Susceptibility Analysis For Marine Aquarium Fish, Gabrielle A. Baillargeon, Alice A. Wynn, Jemelyn Grace P. Baldisimo, Michael F. Tlusty, Andrew L. Rhyne

Biological Sciences Faculty Publications

The marine aquarium trade (MAT) is a significant global industry harvesting millions of wild-caught, live coral reef fishes for public and private aquaria markets in the United States and Europe annually, while supporting fisher livelihoods in the Indo-Pacific. This diverse and species-rich trade is considered data-limited, creating barriers to quantifying the current and future socio-ecological sustainability of the fishery. We present a revised and expanded productivity–susceptibility analysis (PSA) that serves as a holistic risk assessment to estimate the vulnerability of marine aquarium fish to overfishing. Our global analysis includes 306 species that are actively in trade. Improvements to the PSA …

Challenging And Diagnosing Structured Population Models By Testing Predictions From Stochastic Demography, Stephen P. Ellner, Robin E. Snyder, Daniel T. Blumstein, Dylan Z. Childs, Joshua C. Fowler, Christina M. Hernández, Julien G. A. Martin, María Paniw, Yngvild Vindenes

Biological Sciences Faculty Publications

1. Structured population models are parameterized to accurately project expected population sizes, stage/state distributions and population growth rates, but they also predict the variation in outcomes among individuals, such as the variance and skewness of lifetime reproductive output (LRO) and lifespan, the probability of never reproducing, and many other life-history metrics.

2. Testing such predictions about individual outcomes can be very useful model 'stress tests', because they depend on how components of the model (e.g. submodels for survival and fecundity) interact over multiple time steps, not just on the accuracy of the submodels. Because data on among-individual variation is rarely …

Herbivore Identity And Species Richness Shape Fruit Chemical And Quality Responses To Foliar Herbivory, Xavier Ozowara, Taylor M. Sloey, Susan R. Whitehead

Biological Sciences Faculty Publications

The cascading consequences of foliar herbivory on fruit chemistry and quality remain relatively underexplored, with most existing studies focusing on the effects of only one or two attackers. In this study, we examine how increasing herbivore species richness during foliar herbivory alters strawberry (Fragaria × ananassa Duch) fruit quality and phenolic chemistry. We conducted a greenhouse experiment with single species feeding and different combinations of feeding by three generalist lepidopteran species: Spodoptera frugiperda, Heliothis virescens, Helicoverpa zea. Species fed on leaves for 72 h as fruits ripened, and fully ripe fruits were harvested 72 h after …

Stiffening Of Soft Silicone Upon Deep Uv Treatment As Characterized Using Nanoindentation, Amanda Wilder, Zaria Booth, Caden Obermeyer, Saika Sharmin, Venkat Maruthamuthu

Mechanical & Aerospace Engineering Faculty Publications

Silicones are elastomers that have a wide variety of uses, including biomedical applications such as the coating of biomedical devices and as implants. Soft silicones with mechanical properties similar to those of biological tissues have particularly gained use as substrates for cell culture in mechanobiology studies. In this context, it would be desirable to be able to alter their surface mechanical properties with a relatively simple physical treatment. While deep ultraviolet (deep UV) or ultraviolet C (UV-C) treatment has been previously used as a surface treatment method for stiffer silicones formulations, the effect of this treatment on soft silicones relevant …

Performance Analysis And Optimization Of Fructose Memristor-Based Neuromorphic Systems, Harshvardhan Uppaluru, Shakil Mahmud Jiban, Shah Zayed Riam, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic memristors have demonstrated promising synaptic behavior, positioning them as strong candidates for synaptic devices in neuromorphic systems. This paper presents the fabrication and evaluation of a neuromorphic system based on natural organic 16-level and 32-level fructose memristors. First, the manufacturing process of fructose memristors is described in detail. Second, the nonlinear property associated with fructose memristors is investigated, and an optimization method is applied to address the nonlinear effects. The performance of the fructose memristor-based neuromorphic system on MNIST with a multi-layer perceptron and on CIFAR-10 with VGG-8 is evaluated and reported under various conditions -with/without nonlinearity optimization …

Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is a crucial investigative technique used across diverse fields to achieve high-precision measurements. It works by analyzing the phase difference between two interfering waves, which results from variations in optical path lengths within an interferometer. We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer, importantly, with the added advantage of a controllable enhancement factor. This approach is achieved through a two-step process: first, the optical phase difference is encoded into a sub-GHz radiofrequency (RF) signal using microwave-photonic manipulation; then, RF interferometry-assisted phase amplification is implemented at the destructive interference point. In …

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …

Honey-Cnt Memristive Artificial Synaptic Device For Sustainable Neuromorphic Computing System, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru, Jinhui Wang, Kuan Yew Cheong, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, with the advantages of sustainability, environmentally friendliness, and low-cost manufacturing. In this study, carbon nanotubes (CNTs) are added in honey to fabricate honey-CNT memristive artificial synaptic devices. Honey-CNT film is characterized by micro-Raman spectroscopy and the distribution of CNT bundles embedded in the honey-CNT composite layer by cross-sectional scanning electron microscopy for the first time. Critical synaptic functions of the honey-CNT memristor, including spike-rate-dependent plasticity, spike voltage dependent plasticity, learn-forget-relearn, and supralinear spatial summation are revealed, …

Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

This study explores the development of Human Activity Recognition (HAR) systems capable of identifying suspicious activities to enhance security in public spaces. We propose an innovative solution that integrates LiDAR sensors with deep learning technologies. Our method employs advanced models operating on LiDAR point cloud, PV-RCNN for human detection, and LidarGait++ for classifying activities into categories such as standing or walking (non-suspicious) and sneaking or fighting (suspicious). Due to the scarcity of suitable real-world datasets for training such systems, we utilize a 3D simulation tool, Blender, to create realistic environments and generate labeled point cloud data. This synthetic dataset allows …

Trigonometric Continuous-Variable Gates And Hybrid Quantum Simulations Of The Sine-Gordon Model, Tommaso Rainaldi, Victor Ale, Matt Grau, Dmitri Kharzeev, Enrique Rico, Felix Ringer, Pubasha Shome, George Siopsis

Physics Faculty Publications

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present an ancilla-based framework for implementing trigonometric gates with arguments given by arbitrary Hermitian functions of qumode quadratures. The protocol yields unitary gates deterministically, and non-unitary gates through probabilistic post-selection. As a concrete application, we develop a hybrid …

Using Maximum Entropy (Maxent) Tool In Arcgis Pro For Species Distribution Modelling Of Pseudoscorpions In The Pacific Northwest, Elliot Toshihiro Cochran

Masters in GIS Practicum Reports

The use of Geographic Information Systems (GIS) to create Species Distribution Models (SDMs) is rising among many scientific disciplines. Many professionals who were not originally focused on GIS are increasingly becoming more invested in this technology. SDMs are widely used to estimate species’ potential geographic distributions and to evaluate the environmental factors that constrain their ranges. The presence-only maximum entropy (MaxEnt) algorithm implemented in the MaxEnt tool in ArcGIS Pro was used in this project to model habitat suitability for two species of pseudoscorpions, M. pacificus and an undescribed species, in Oregon and Washington. Presence points (of specimen sample locations) …

Predicting Oil Contamination In Water Using Machine Learning On Microbial Compositions, Tong Gao, Isaac Bigcraft, Stephen Techtmann, Issei Nakamura

Michigan Tech Publications

We present a compact and generative machine-learning framework that predicts oil contamination based on microbial community compositions from experimental samples. Our method combines dimensionality reduction with data augmentation and generative modeling to address high-dimensional, non-linear, and sparse microbial data. To reduce the 503-dimensional bacterial composition dataset, we compared three dimensionality reduction techniques: feature importance from random forest, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE). Feature importance outperformed PCA and t-SNE, improving predictive performance and identifying microbial species most strongly correlated with oil contamination. To mitigate data scarcity, we augmented the training data using an augmented data neural …

Long‑Term Impacts Of A Composted Sewage Sludge–Based Class B Organic Fertilizer On Soil Micronutrients And Crop Production In The Tropics, Luana Corrêa Silva, Aline Renée Coscione, Rodrigo Silva Alves, Philippe Solano Toledo Silva, Adrielle Rodrigues Prates, Leiliane Dutra Silva, Fabrício Da Silva Vasconcelos, Jussara Borges Regitano, Cassio Hamilton Abreu-Junior, Wanderley José De Melo, Gian Franco Capra, Arun Dilipkumar Jani, Thiago Assis Rodrigues Nogueira

Biology, Agriculture and Chemistry Faculty Publications and Presentations

Organic fertilizers, such as Class B materials (e.g., composted sewage sludge, CSS), may contain high levels of plant micronutrients, but their use in crop production needs to be monitored to avoid environmental problems. In this study, we sought to understand the Cu, Mn, and Zn dynamics in tropical soils and their residual effects on maize and wheat productivity, after three CSS applications. A randomized complete block experimental design with six treatments and four replicates was implemented. CSS rates (0.0, 5.0, 7.5, 10.0, and 12.5 Mg ha⁻¹) were compared with conventional mineral fertilizer (CMF). Over a six-year period encompassing …

The Role Of Soil In Historical Warfare: A Review, Gian Franco Capra, T. A.R. Nogueira, Cassio Hamilton Abreu-Junior, Arun Dilipkumar Jani, Rafael Barroca Silva, Eleonora Grilli, Alessandro Auzzas, Antonio Ganga

Biology, Agriculture and Chemistry Faculty Publications and Presentations

Soil has played a fundamental yet undervalued role in shaping the fate of historical warfare. While the effects of war on the soil environment have been thoroughly investigated, the impact of soil on military strategies and battle outcomes remains poorly understood. This review aims to: i) explore the multifaceted role of soil in warfare, focusing on its impact on several aspects (mobility, fortifications, camouflage, health, geopolitical strategy, etc.); ii) identify which soil types were usually most associated with conflicts, and iii) how soil features influenced military decision-making. A dataset of over 17,000 recorded battles (1468 BCE–2003) was …

Ecological Feedbacks In The Earth System, Eugene J. Murphy, Jessica J. Williams, Isla H. Myers-Smith, Vivienne P. Groner, David M. P. Jacoby, Lester Kwiatkowski, Jess Melbourne-Thomas, Emma Ransome, Cristina Banks-Leite, Laurent Bopp, Marion Gehlen, Eileen E. Hofmann, Babette Hoogakker, Nadine M. Johnston, Yadvinder Malhi, Emma L. Cavan

CCPO Publications

Ecological feedbacks are fundamental features of the Earth system, affecting physical processes and chemical cycles. Our understanding of the interactions underlying these feedbacks at different spatial and temporal scales and the extent to which feedbacks affect Earth system functioning remains limited. Climate change and other anthropogenic pressures are already negatively affecting ecological processes in marine, freshwater, and terrestrial ecosystems. These will most likely be amplified in the coming decades under our current warming and socioeconomic pathways. The knock-on impacts on ecological feedbacks have the potential to cause rapid perturbations to the Earth system, and may significantly impact the structure and …

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 …