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Articles 1 - 30 of 139
Full-Text Articles in Applied Statistics
A Predictive Coding Account Of Spatial Working Memory Following Prophylactic Levetiracetam Administration Prior To Traumatic Brain Injury, Omeima Mutwali
A Predictive Coding Account Of Spatial Working Memory Following Prophylactic Levetiracetam Administration Prior To Traumatic Brain Injury, Omeima Mutwali
Dissertations, Theses, and Capstone Projects
Traumatic brain injury (TBI) symptom prevention and remediation is an important area of research that would benefit vulnerable groups, including active-duty and veteran soldiers. These patients can sustain penetrative forces in fields of combat or in training, which result in focal lesions that trigger inflammatory and degenerative processes in the brain. Both primary and secondary injuries are associated with changes to cognition, behavior and affective state. This disease poses increased risk of epileptogenesis, as well. Given these outcomes, prior research has evaluated levetiracetam (LEV) as a prophylactic treatment for seizures, cognitive deficits and negative emotionality. LEV acts as a presynaptic …
Machine Learning-Based Spatio-Temporal Modeling Of Climate Dynamics And Desertification In The Sahara–Sahel Region, Stephen M. Tivenan
Machine Learning-Based Spatio-Temporal Modeling Of Climate Dynamics And Desertification In The Sahara–Sahel Region, Stephen M. Tivenan
Theses and Dissertations
Arid climate classifications are threshold-dependent and easily interpretable mappings that are widely used in ecological, agricultural, and climate-related studies. These classifications inform scientific understanding, support policy and land management decisions, and provide an intuitive summary of environmental conditions. Despite their usefulness, traditional arid climate classifications often fail to quantify uncertainty, incorporate spatial context, or account for complex relationships among relevant environmental variables. Existing approaches to uncertainty assessment have largely relied on comparing classifications across multiple datasets or alternative formulas, but these methods generally overlook important spatial dependence and latent structure in the data.
This dissertation develops three machine learning-based statistical …
[Kyda] Biologically Grounded Surrogate-Driven Parameter Inference For Sparsely Observed Dynamical Systems, Joshua C. Macdonald
[Kyda] Biologically Grounded Surrogate-Driven Parameter Inference For Sparsely Observed Dynamical Systems, Joshua C. Macdonald
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Mentoring First-Year Stem Students Through Collaborative Research In The Haynes Scholars Program, Alex Capaldi, Laura Tipton
Mentoring First-Year Stem Students Through Collaborative Research In The Haynes Scholars Program, Alex Capaldi, Laura Tipton
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Evaluating Alpha Spending Functions Applied To Observational Time-To-Event Analysis, Moses Torgbenu
Evaluating Alpha Spending Functions Applied To Observational Time-To-Event Analysis, Moses Torgbenu
Electronic Theses and Dissertations
This thesis explores the theoretical foundation of the alpha spending approach and extends its application beyond the conventional setting of randomized controlled trials (RCTs) to observational studies with time to event analyses. In these less structured environments, key design parameters such as the total number of events are often unknown, posing challenges for the standard implementation of sequential analysis methods.
Through simulation studies, this research delivers several important contributions. First, it presents a modified approach that uses calendar time to define the timing of interim analyses while relying on event-based information to estimate the correlation among test statistics. This adjustment …
The Nature Of Anthropogenically Driven River Drying: Spatiotemporal Causes And Consequences, Eliza Inez Gilbert
The Nature Of Anthropogenically Driven River Drying: Spatiotemporal Causes And Consequences, Eliza Inez Gilbert
Biology ETDs
Streambed drying naturally occurs in over 60% of rivers and streams worldwide. Climate change and human regulation of surface and groundwater have increased drying in naturally intermittent systems and caused perennial systems to transition to intermittency, impacting water security, water quality, and biodiversity. To understand human-induced drying dynamics, we used 12 years of daily drying data along a 154-km regulated reach of the Rio Grande. We conceptualized river drying as a regime analogous to the natural flow regime paradigm and quantified drying magnitude, rate of change, and duration. Although linear models predicting drying magnitude and rate of change were uninterpretable, …
Evaluating Predictive Models For Predicting Total Score Of Beef Carcasses, Emmanuel Forson
Evaluating Predictive Models For Predicting Total Score Of Beef Carcasses, Emmanuel Forson
Electronic Theses and Dissertations
The beef industry plays a vital role in global agriculture, with carcass quality and consumer preference being key determinants of market success. This thesis examines predictive modeling techniques for estimating the Total Score of beef carcasses, a composite measure representing yield and quality, primarily used by the Nebraska Cattlemen Association. Using data from the Nebraska Cattlemen’s Foundation Retail Value Steer Challenge (2000–2023), the study compares the performance of First Order Multiple Linear Regression (MLR) with three machine learning techniques: K-Nearest Neighbors (KNN), Random Forest, and Gradient Boosting Machine (GBM).
The analysis focuses on six key predictors: Hot Carcass Weight, Back …
Leveraging Historical Data For Estimating Genetic Gain And Implementing Genomic Selection In A Student Led Barley Breeding Program, Sydney Graham
Leveraging Historical Data For Estimating Genetic Gain And Implementing Genomic Selection In A Student Led Barley Breeding Program, Sydney Graham
Department of Statistics: Dissertations, Theses, and Student Research
In Nebraska, winter feed barley presents an emerging market for producers and an opportunity to diversify cropping systems. The University of Nebraska Barley Breeding Program aims to develop high-yielding, winter-hardy varieties. A unique aspect of this program is that doctoral students serve as barley breeders and are responsible for crossing, data collection, and advancement decisions. While this provides hands-on experience for the students, the impact of student leadership has not been examined.
This study used a historical data set to evaluate the realized genetic gain of the breeding program, and as a training population for genomic selection. The dataset consisted …
Linking Water Quality And Climate Change To Long-Term Trends In Species Abundance In Norwalk Harbor, Viktoria Savatorova, Aidan Kieft, Nicole C. Spiller, Kasey Burns
Linking Water Quality And Climate Change To Long-Term Trends In Species Abundance In Norwalk Harbor, Viktoria Savatorova, Aidan Kieft, Nicole C. Spiller, Kasey Burns
Spora: A Journal of Biomathematics
This study examines the effects of environmental changes on fish populations in Norwalk Harbor, focusing on winter flounder (Pseudopleuronectes americanus), cunner (Tautogolabrus adspersus), northern pipefish (Syngnathus fuscus), and naked goby (Gobiosoma bosci) as examples of species responding to climate-related shifts. We analyze how water temperature, salinity, and dissolved oxygen correlate with fish abundance. To assess statistically significant differences in catch per unit effort (CPUE) across harbor regions, we applied the Kruskal-Wallis test followed by Dunn's post-hoc test. Seasonal variations in CPUE were examined by comparing monthly catch data for each species. K-means …
Methods In Statistics, Machine Learning, And Deep Learning For Combining Multi-Omics Dataset, Md Mutasim Billah
Methods In Statistics, Machine Learning, And Deep Learning For Combining Multi-Omics Dataset, Md Mutasim Billah
Dissertations, Master's Theses and Master's Reports
Transcriptome-wide association studies (TWAS) have emerged as a powerful strategy to bridge genome-wide association studies (GWAS) with gene regulatory mechanisms by integrating genotypic data with gene expression data. While early TWAS methods typically rely on linear models and single-tissue expression references, recent advances underscore the need for flexible, multi-tissue approaches that can capture heterogeneous regulatory architectures and tissue-specific expression patterns. This dissertation introduces a three‑part research project that advances multi‑tissue transcriptome‑wide association studies (TWAS) along complementary axes of methodology, statistical power, and modelling flexibility.
In chapter One, TWAS‑CTL introduces a two‑stage cross‑tissue learner that trains any user‑chosen single‑tissue imputers (STLs) …
“Regression To The Mean”: The Confluence Of Eugenics And Statistics In The 19th And 20th Centuries, Emrys G. King
“Regression To The Mean”: The Confluence Of Eugenics And Statistics In The 19th And 20th Centuries, Emrys G. King
Pomona Senior Theses
The work of this thesis is twofold — first, qualitatively characterizing the confluence between the British eugenics and statistics movements in the late 19th and early 20th centuries, and second, quantitatively analyzing the effect of this foundation on pedagogical materials in the growing field of statistics between 1880 and 1970. Towards the first goal, the history of the method of least squares, state statistics, and positive and negative eugenics are outlined, followed by a close reading of the foundational texts authored by Francis Galton and Karl Pearson that introduced linear regression. Towards the latter goal, English-language statistics textbooks published between …
A Method For Empirically Assessing Small Area Estimators Via Bootstrap-Weighted K-Nearest-Neighbor Artificial Populations, With Applications To Forest Inventory, Grayson W. White, Jerzy Wieczorek, Zachariah W. Cody, Emily X. Tan, Jacqueline O. Chistolini, Kelly S. Mcconville, Tracey S. Frescino, Gretchen G. Moisen
A Method For Empirically Assessing Small Area Estimators Via Bootstrap-Weighted K-Nearest-Neighbor Artificial Populations, With Applications To Forest Inventory, Grayson W. White, Jerzy Wieczorek, Zachariah W. Cody, Emily X. Tan, Jacqueline O. Chistolini, Kelly S. Mcconville, Tracey S. Frescino, Gretchen G. Moisen
Faculty Journal Articles
National Forest Inventories monitor forest attributes across a variety of spatial and temporal scales in a given country. Increased interest in reporting and management at smaller scales has driven National Forest Inventories to investigate and adopt small area estimation (SAE) due to the promise of increased precision at these scales. However, comparing and evaluating SAE models for a given application is inherently difficult. Typically, many areas lack enough data to check unit-level modeling assumptions or to assess unit-level predictions empirically; and no ground truth is available for checking area-level estimates. Design-based simulation from artificial populations can help with each of …
Linking Empirical Data And Numerical Simulation To Characterize Dynamic Fire Behavior Associated With Interacting Firelines, Marta Sergeevna Jerebets
Linking Empirical Data And Numerical Simulation To Characterize Dynamic Fire Behavior Associated With Interacting Firelines, Marta Sergeevna Jerebets
Graduate Student Theses, Dissertations, & Professional Papers
Understanding fuel pattern-fire process relationships is key for predicting fire behavior and effects with follow-on benefits to proactive fire management and model validation. To characterize dynamic fire behavior, this thesis leverages empirical data and numerical simulation through two complementary studies.
In the first study, longwave thermal sensors aboard unmanned aerial systems (UAS) were used to capture fine-scale fire behavior in two experimental grass burns. A novel paired design was used to quantify the effects of fuel arrangement on fire behavior with 3.66 m diameter treatments cut to a height of 0.15 m. The treatments ephemerally reduced fire rate of spread …
Hybrid Mixtures Of Factor Analyzers For High Dimensional Data, Kazeem Abiodun Kareem
Hybrid Mixtures Of Factor Analyzers For High Dimensional Data, Kazeem Abiodun Kareem
Dissertations, Master's Theses and Master's Reports
Factor analysis is a powerful tool for modeling latent structures in high-dimensional data, traditional approaches assume a single global structure, limiting their ability to capture heterogeneity. The Mixture of Factor Analyzers (MFA) extends classical factor analysis by modeling data as a mixture of Gaussian-distributed local subspaces, effectively uncovering cluster-specific latent structures. However, MFA relies on Gaussian mixtures, making it sensitive to outliers and ill-suited for heavy-tailed data. The Mixture of $t$-Factor Analyzers (M$t$FA) addresses these limitations by incorporating multivariate $t$-distributions, improving robustness. Despite their advantages, both MFA and M$t$FA face significant computational challenges in high-dimensional settings, particularly due to costly …
Modeling Neighborhoods As Fuel For Wildfire, Bryce Alan Young
Modeling Neighborhoods As Fuel For Wildfire, Bryce Alan Young
Graduate Student Theses, Dissertations, & Professional Papers
Wildfire models drive billions of dollars in risk mitigation efforts. However, the modeling community currently lacks a representative fuelscape on which to base simulations of fire spread in the built environment and the wildland-urban interface (WUI) where vegetation and structures act together as fuel for wildfire. This thesis advances wildfire risk modeling by addressing the underdeveloped representation of the built environment in existing frameworks. By identifying inconsistencies in how structure and defensible space features are defined and used across empirical studies, predictive indices, and fire spread models, this research lays the groundwork for standardized modeling approaches and feature selection (Chapter …
Impact Of Urban Development On Uv Exposure: A Clustering And Machine Learning Assessment, Taufik Roni Sahroni Mr., Verdi Yasin, Lulut Alfaris, Reza Ariefka, Ruben Cornelius Siagian, Mohammad Alfin Karim, Nana Rahdiana, Ade Suhara
Impact Of Urban Development On Uv Exposure: A Clustering And Machine Learning Assessment, Taufik Roni Sahroni Mr., Verdi Yasin, Lulut Alfaris, Reza Ariefka, Ruben Cornelius Siagian, Mohammad Alfin Karim, Nana Rahdiana, Ade Suhara
Journal of Environmental Science and Sustainable Development
The relocation of Indonesia's capital city is anticipated to promote inclusive economic growth while embracing cultural diversity. However, this transition may affect ultraviolet (UV) radiation exposure patterns. The study investigated variations in UV exposure in the IKN region, focusing on urban development factors such as land use and population density that affect public health, sun protection, and skin cancer prevention. The research hypothesized that UV radiation is significantly correlated with these factors. UV Index data from 2010-2023, a hierarchical clustering method, identifies complex data patterns without determining the number of clusters. XGBoost, a machine learning model, was used for handling …
Comparison Of Statistical And Machine Learning Genomic Prediction Methods In Plant Breeding: Case Studies In Maize And Soybean, Igor Kuivjogi Fernandes
Comparison Of Statistical And Machine Learning Genomic Prediction Methods In Plant Breeding: Case Studies In Maize And Soybean, Igor Kuivjogi Fernandes
Graduate Theses and Dissertations
Plant breeding is essential to increase genetic gain and food production worldwide. This study was conducted to evaluate new ways to use machine learning (ML) to tackle plant breeding challenges, where two ideas were tested — the first chapter focuses on how to combine genetic and environmental data using ML to improve the prediction of maize grain yield in multi-environment trials, while the second chapter centers on how to couple feature selection of molecular markers with ML to enhance prediction of yield in soybean, and, in both cases, ML approaches were compared to well-established statistical methods greatly adopted by the …
High Fat Diet & Social Isolation: Interactive Effects On Pain, Cognition, & Neuroinflammation, Ian M. Campuzano
High Fat Diet & Social Isolation: Interactive Effects On Pain, Cognition, & Neuroinflammation, Ian M. Campuzano
Research Psychology Theses
Prior research has established a role for both social isolation and exposure to high fat Western diets in altering a range of behaviors from reduced memory performance to increased depression-like behaviors. The present study scrutinizes the interplay among these variables during the peri-adolescent developmental phase, utilizing Long-Evans rats as the experimental model. Our overarching hypothesis is that rats exposed to either social isolation, a high-fat diet, or both will result in heightened pain sensitivity, diminished cognitive flexibility, and increased neuroinflammatory responses within brain regions implicated in sociability, cognition, memory, and pain processing. Behavioral flexibility will be assessed using a maze-based …
Evaluating Past Progress And Assessing Prediction Breeding Strategies For Sustained Genetic Gains In The Louisiana Sugarcane Variety Development Program, Brayden A. Blanchard
Evaluating Past Progress And Assessing Prediction Breeding Strategies For Sustained Genetic Gains In The Louisiana Sugarcane Variety Development Program, Brayden A. Blanchard
LSU Doctoral Dissertations
The aim of this dissertation is to outline important considerations for the Louisiana Sugarcane Variety Development Program (LSVDP) as it pertains to historical progress, impact, goal setting, and new strategies for continued genetic gains. Industry progress was evaluated with robust regression models to quantify rates of productivity gains. Over the last 50 years, statistically significant productivity gains were identified in sucrose content (45%), cane yield (32.2%), and sugar yield (93%) while pairwise comparisons of decades showed that progress was incremental rather than rapid and sustained once achieved. The decade from 1990-1999 was identified as the only decade with a significant …
Morphometric Analysis And Taxonomic Re-Evaluation Of Pepsis Cerberus Lucas And P. Elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini), Frank E. Kurczewski, Akira Shimizu, Diane H. Kiernan
Morphometric Analysis And Taxonomic Re-Evaluation Of Pepsis Cerberus Lucas And P. Elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini), Frank E. Kurczewski, Akira Shimizu, Diane H. Kiernan
Insecta Mundi
Hurd (1952) separated Pepsis cerberus Lucas from P. elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini) based on external morphology and biogeography. Vardy (2005) synonymized the familiar and historically well-documented P. cerberus and P. elegans, combining these Nearctic taxa with several Neotropical variants in an extremely broad definition of P. menechma Lepeletier. In doing so, Vardy (2005) breached the principle of nomenclatural stability. He ignored the prevailing usage and clearly violated articles 23.2, 23.3 and 23.9.1.2 of the ICZN (1999). Morphological differences, ecological divergence, and narrow sympatric geographic distribution of P. cerberus and P. elegans …
Multi-Type Branching Processes In Time-Varying Environments, Arash Jamshidpey
Multi-Type Branching Processes In Time-Varying Environments, Arash Jamshidpey
Biology and Medicine Through Mathematics Conference
No abstract provided.
Evaluating The Epidemiological, Hormonal, And Psychosocial Sex-Based Differences In Sports-Related Concussion Outcomes, Samantha Kanny
Evaluating The Epidemiological, Hormonal, And Psychosocial Sex-Based Differences In Sports-Related Concussion Outcomes, Samantha Kanny
All Dissertations
Sports-related concussions (SRCs) affect approximately 3.8 million athletes in the United States per year. A multitude of risk factors including age, sex, concussion history and prior medical conditions have been observed to significantly increase sports-related concussion symptom burden. Researchers have posited many reasons to explain sex-based differences in SRC outcomes, often categorized by biological characteristics or sociocultural factors, however, females are vastly underrepresented in sports-related concussion research, making it difficult to understand the true mechanisms underlying SRC sex-based differences. The goal of this dissertation is to help fill the current gap in knowledge on sex-based differences in sports-related concussion outcomes. …
Benthic Community Response To The Impacts Of Proposed Sediment Diversions In Louisiana Estuaries, Jillian C. Tupitza
Benthic Community Response To The Impacts Of Proposed Sediment Diversions In Louisiana Estuaries, Jillian C. Tupitza
LSU Doctoral Dissertations
Sediment diversions designed to mitigate land loss in coastal Louisiana will likely cause ecosystem-wide shifts. The first diversion, planned for Barataria Bay, will divert fresh water and sediment from the Mississippi River into the surrounding wetlands to help them keep pace with high rates of relative sea-level rise (RSLR). Estuarine benthic communities were used in this study as tools to characterize ecological patterns in the context of anticipated salinity changes. I reviewed relevant literature, conducted a two-year survey of Barataria Bay benthos, executed a reciprocal transplant experiment to describe changes that might occur in both community composition and trophic dynamics, …
Application And Effectiveness Of Artificial Intelligence For The Border Management Of Imported Frozen Fish In Taiwan, Wen-Chin Tu, Wan-Ling Tsai, Chi-Hao Lee, Chia-Fen Tsai, Jen-Ting Wei, King-Fu Lin, Shou-Mei Wu, Yih-Ming Weng
Application And Effectiveness Of Artificial Intelligence For The Border Management Of Imported Frozen Fish In Taiwan, Wen-Chin Tu, Wan-Ling Tsai, Chi-Hao Lee, Chia-Fen Tsai, Jen-Ting Wei, King-Fu Lin, Shou-Mei Wu, Yih-Ming Weng
Journal of Food and Drug Analysis
In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these border sampling inspections. Previously, border management has used an automated border inspection system (import food inspection (IFI) system) to select batches via a random sampling method to manage the risk levels of various food products complying with regulatory inspection procedures. Several countries have implemented artificial intelligence (AI) technology to improve domestic governmental processes, social service, and public feedback. AI technologies are applied in border inspection by the Taiwan Food and Drug Administration (TFDA). Risk management of border inspections …
A Causal Inference Approach For Spike Train Interactions, Zach Saccomano
A Causal Inference Approach For Spike Train Interactions, Zach Saccomano
Dissertations, Theses, and Capstone Projects
Since the 1960s, neuroscientists have worked on the problem of estimating synaptic properties, such as connectivity and strength, from simultaneously recorded spike trains. Recent years have seen renewed interest in the problem coinciding with rapid advances in experimental technologies, including an approximate exponential increase in the number of neurons that can be recorded in parallel and perturbation techniques such as optogenetics that can be used to calibrate and validate causal hypotheses about functional connectivity. This thesis presents a mathematical examination of synaptic inference from two perspectives: (1) using in vivo data and biophysical models, we ask in what cases the …
Exact Testing For Heteroscedasticity In A Two-Way Layout In Variety Frost Trials When Incorporating A Covariate, Angelika A. Pilkington, Brenton R. Clarke, Dean A. Diepeveen
Exact Testing For Heteroscedasticity In A Two-Way Layout In Variety Frost Trials When Incorporating A Covariate, Angelika A. Pilkington, Brenton R. Clarke, Dean A. Diepeveen
Grain and Other Field Crops Research Articles
Two-way layouts are common in grain industry research where it is often the case that there are one or more covariates. It is widely recognised that when estimating fixed effect parameters, one should also examine for possible extra error variance structure. An exact test for heteroscedasticity, when there is a covariate, is illustrated for a data set from frost trials in Western Australia. While the general algebra for the test is known, albeit in past literature, there are computational aspects of implementing the test for the two way when there are covariates. In this scenario the test is shown to …
Influence Of Attack Performance On The Ovc Volleyball Regular Seasons 2022 & 2023, Ignacio Valdemoros
Influence Of Attack Performance On The Ovc Volleyball Regular Seasons 2022 & 2023, Ignacio Valdemoros
Masters Theses
Understanding the outcome of volleyball games is necessary for coaches before, after, and during a season. There are several ways to gain this understanding, but statistical analysis is fundamental to see the minimum patterns of behavior that influence wins and losses in Volleyball. Furthermore, this analysis helps identify the optimal approach to achieving a goal and determining the most effective alternative to success. Scoring points in Volleyball involves three key skills: serving, blocking, and attacking. Among these skills, attacking plays the most relevant role in determining the outcome of a match. The position on the court (e.g. Outside Hitter, Middle …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
Occupational And Environmental Factors Influencing Morale Of United States Federal Wildland Firefighters, Rachel M. Granberg, Ting Shen, Seth W. Pearson, Robin M. Verble
Occupational And Environmental Factors Influencing Morale Of United States Federal Wildland Firefighters, Rachel M. Granberg, Ting Shen, Seth W. Pearson, Robin M. Verble
Psychological Science Faculty Research & Creative Works
Background. Wildland firefighters have physically and psychologically demanding jobs that can result in social, economic and health-related stress. Previous studies have examined the physiological and physical effects of a career in wildland fire, but fewer studies have addressed psychological effects, and to date, none have directly analyzed the hiring and work experiences of wildland firefighters. Aims. We surveyed work experiences, health and well-being, and morale of wildland firefighters, explored factors that can improve recruitment and retention, and summarized broad patterns. Methods. We conducted a voluntary anonymous survey of 708 federal wildland firefighters via an online platform over 2 months in …
Baa-Ttling Sore Mouth In Sheep With Mathematical Modeling, David C. Elzinga, W. Christopher Strickland
Baa-Ttling Sore Mouth In Sheep With Mathematical Modeling, David C. Elzinga, W. Christopher Strickland
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.