Physical Sciences and Mathematics Commons^™

The Concept Of T-Basis And Vector-Valued Hardy Classes, Bilal Bilalov, Sabina Rahib Sadigova

Turkish Journal of Mathematics

This paper introduces the concept of a t-basis generated by some bilinear mapping t(·;·). It is considered the vector-valued class L_p(X) := L_p(J; X), 1 ≤ p < +∞, where J = [−π, π] and X is a Banach space with the UMD property, and it is proven that the classical system of exponents {e^int}_n∈ℤ forms a t-basis for L_p(X), 1 < p < +∞. Using this fact, the Hardy vector classes _nH_p^±(X), 1 < p < +∞, different from the classical ones, are defined, and an equivalent definition of these classes is given and some of their properties are studied. In addition, the concept of t-Riesz property of a system of exponentials is introduced in L_p(X), 1 < p < +∞, and it is proved that this system has the t-Riesz property. A new method is given for establishing the Plemelj–Sokhotski formulas for X-valued Cauchy type integrals when X has the UMD property. An abstract analogue of the “1/4-Kadets” theorem is obtained for …

Predicting Battery Levels Of Sensor Nodes Using Reinforcement Learning In Harsh Underground Mining Environments, Manish Anand Yadav, Mohamed Elmahallawy, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Underground mining is a hazardous environment, with frequent accidents leading to significant loss of life each year. To enhance safety, sensor nodes monitor key environmental factors such as temperature, toxic gases, and miners' locations, as well as transmit critical messages. Miners interact with these sensors, which track their movements, enabling their location to be determined even without GPS signals. Therefore, predicting the battery life of these sensors is essential for: (i) rerouting miners during emergencies, (ii) ensuring timely maintenance, and most importantly (iii) identifying sensors that need energy harvesting to maintain vital communication within the mine. In this work, we …

Independent Vs. Signed Musicians: Does Thier Status Affect Their Success?, Zachary Vincent

Honors Projects in Mathematics and Economics

As technology has advanced and become more widely available, and as the public learns more about the recording industry and its workings, more musicians are choosing not to sign with record labels, becoming independent musicians. This now raises the question: does a musician’s status of independent or signed determine their level of success? It has been previously found that independent musicians have a more difficult time competing with signed musicians due to the resources provided by record labels and the way labels negotiate with large streaming platforms, giving signed labels more opportunities to be seen in the public eye, but …

Detecting Burn Severity And Vegetation Recovery After Fire Using Dnbr And Dndvi Indices: Insight From The Bosco Difesa Grande, Gravina In Southern Italy, Somayeh Zahabnazouri, Patrick Belmont, Scott David, Peter E. Wigand, Mario Elia, Domenico Capolongo

Watershed Sciences Faculty Publications

Wildfires serve a paradoxical role in landscapes—supporting biodiversity and nutrient cycling while also threatening ecosystems and economies, especially as climate change intensifies their frequency and severity. This study investigates the impact of wildfires and vegetation recovery in the Bosco Difesa Grande forest in southern Italy, focusing on the 2017 and 2021 fire events. Using Google Earth Engine (GEE) accessed in January 2025, we applied remote sensing techniques to assess burn severity and post-fire regrowth. Sentinel-2 imagery was used to compute the Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI); burn severity was derived from differenced NBR (dNBR), and …

Combining N-Mixture And Occupancy Analysis Offers A More Complete Picture Of Carnivore Habitat Use In Northeastern Türkiye, J. David Blount, Austin M. Green, Mark Chynoweth, Emrah Çoban, Josip Kusak, Çağan H. Şekercioğlu

Wildland Resources Faculty Publications

Occupancy and N-mixture analyses have been successfully used to understand habitat use in various species. However, since these methods fundamentally answer different questions about wildlife distribution, the results from each modelling approach may provide different insights into species’ habitat use. In this study, we leveraged data from a long-term camera trapping study in northeastern Türkiye to compare the results from occupancy and N-mixture analyses, with the main objective of understanding how the modelling approach used can influence our knowledge of species’ habitat use. Specifically, we compared the habitat use preferences from N-mixture and occupancy analyses for three carnivore species with …

Life Cycle Assessment Of Co-Located Floating Solar And Offshore Wind, Danela Sadikaj, Meghann Smith

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Is combining floating solar and offshore wind platforms feasible for increasing energy capacity while displacing the environmental impacts that each of these systems has independently? In recent years offshore wind has become a very popular option to decarbonize the energy sector without overtaking valuable land. While floating solar is not a new technology, using solar in a marine environment is still in an experimental phase. This research proposes a Life Cycle Assessment (LCA) model of co-located solar technology within the proposed offshore wind farms near New Jersey’s coastline. While both technologies themselves are zero-emission while operating, they each require a …

Evaluation Of Topographic Effect Parameterizations In Weather Research And Forecasting Model Over Complex Mountainous Terrain In Wildfire-Prone Regions, Yonghan Jo, Seung Hee Kim, Yungon Lee, Changki Kim, Jinkyu Hong, Junhong Lee, Keunchang Jang

Institute for ECHO Articles and Research

Recent trends of intense forest fires in the Korean Peninsula have increased concerns about more extreme burning in the future under a warming climate. Accurate and reliable fire weather information has become more critical to reduce the risk of forest-related disasters over complex terrain. In this study, two parameterizations reflecting complex topographic effects were implemented in the Weather Research and Forecasting (WRF) model. The model performance was evaluated over the mountainous region in Gangwon-do, South Korea’s most significant forest area. The simulation results of the wildfire case in 2019 show that subgrid-scale orographic parameterization considerably improves model performance regarding wind …

Patterns In Tropical Cyclone Intensity And Frequency Since 1960, Ramie E. Thompson

Student Scholarship

Tropical cyclones, also known as hurricanes or typhoons, are defined as organized storm systems that form in the warm waters around the equator (NOAA, 2024). This happens due to the combination of warm waters, light winds, and preexisting weather conditions. In the last 50 years, tropical cyclones have accounted for approximately 800,000 deaths and an economic loss of $1.4 trillion USD due to their resulting damages (WMO, 2024). Research in this field includes studies that encompass a variety of time scales including from 85 to 150 years on a global or regional level and studies that focus on more recent …

Reducing Emissions And Increasing Resource Efficiency In Offshore Wind Turbines: Insight From Life Cycle Analysis, Jean Claire Pineda, Meghann Smith

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Globally, offshore wind (OSW) has been identified as a key technology for decarbonization. While OSW’s development timeline remains uncertain in the United States, New Jersey has set the ambitious goal of 11 GW by 2040. OSW produces zero carbon emissions; however, it relies heavily on resource-intensive materials like steel, rare earth elements, and copper, and manufacturing those materials have numerous environmental impacts, including carbon emissions. Supply chain disruptions—from COVID-19, rising material costs, and geopolitical challenges—add further complexity. Previous research modelled the environmental impacts of Atlantic Shores OSW South Project with an established domestic supply chain, producing 0.013kg CO2 per kWh. …

Extending The Bridge Connecting Chiral Lagrangians And Qcd Gaussian Sum Rules For Low-Energy Hadronic Physics, Amir H. Fariborz, Jason N.E. Ho, T. G. Steele

Faculty Work Comprehensive List

It has previously been demonstrated that the mesonic fields in chiral Lagrangians can be related to the quark-level operators of QCD sum-rules via energy-independent (constant) scale factor matrices constrained by chiral symmetry. This leads to universal scale factors for each type of chiral nonet related to quark-antiquark (𝑞⁢¯𝑞) operators and four-quark (𝑞⁢𝑞⁢¯𝑞⁢¯𝑞) operators. Motivated by these successful demonstrations of scale-factor universality for the 𝐾*0 isodoublet and 𝑎0 isotriplet scalar mesons, a revised Gaussian QCD sum rule methodology is developed that enables the extension to higher-dimensional isospin sectors, including the possibility of mixing with glueball components. Moreover, to extract nonperturbative information …

Visualization Of Coastal Carbonate Lithosomes: Color-Intensity Patterns And Georadar Imaging Of A Semi-Lithified Strandplain, Eleuthera Island, The Bahamas, Ilya Buynevich, Michael Savarese, H. Allen Curran

Geosciences: Faculty Publications

Quaternary carbonate strandplains serve as archives of land–sea interaction, including the impacts of storms and tsunamis. Incipient lithification, especially of compound beach/dune ridges within the action zone of salt spray, presents challenges to geological research, which is often limited to exposures. This study combines aerial image analysis with geophysical datasets to assess the morphostratigraphy and internal structure of the Freedom Beach Strandplain along southern Eleuthera Island, The Bahamas. Color-intensity analysis of field photographs and satellite images revealed general patterns that can be used to distinguish between areas with different grayscale parameters (sand-covered surfaces, lithified ridges, vegetation, etc.). Cross-shore (dip-section) high-resolution …

Algorithms To Estimate Contours: Two Applications Of Analytical Tools In Differential Geometry And Topology, Mohammad Abirul Islam

Computer Science ETDs

We develop distributed robotics algorithms with analytical tools needed to define and analyze angle turned and distance traversed by robots executing geometric algorithms. We then use these analytical tools to obtain information, via sensor measurements, about an a priori unknown surface. Our contributions are threefold. First, we develop the Sketch Algorithm, which estimates the boundary of any unknown contour and is asymptotically optimal in terms of distance traversed and angle turned. Second, we present experimental field work that validates the Sketch Algorithm. Finally, we propose an approach to find multiple sources of a surface with potential applications to approximate that …

Incorporating Latent Survival Trajectories And Covariate Heterogeneity In Time-To-Event Data Analysis: A Joint Mixture Model Approach, Fu-Wen Liang, Wenyaw Chan, Michael D Swartz, Bouthaina S Dabaja

Faculty, Staff and Student Publications

Background: Finite mixture models have been recently applied in time-to-event data to identify subgroups with distinct hazard functions, yet they often assume differing covariate effects on failure times across latent classes but homogeneous covariate distributions. This study aimed to develop a method for analyzing time-to-event data while accounting for unobserved heterogeneity within a mixture modeling framework.

Methods: A joint model was developed to incorporate latent survival trajectories and observed information for the joint analysis of time-to-event outcomes, correlated discrete and continuous covariates, and a latent class variable. It assumed covariate effects on survival times and covariate distributions vary across latent …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Residential Metals Abatement Program (Rmap) Quality Assurance Project Plan (Qapp) (Residential Parcels) (Dated February 26, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Analyticity, Superoscillations And Supershifts In Several Variables, Fabrizio Colombo, Irene Sabadini, Daniele C. Struppa, Alain Yger

Mathematics, Physics, and Computer Science Faculty Articles and Research

Superoscillations have roots in various scientific disciplines, including optics, signal processing, radar theory, and quantum mechanics. This intriguing mathematical phenomenon permits specific functions to oscillate at a rate surpassing their highest Fourier component. A different way of thinking about superoscillations consists in realizing that it is possible to reproduce the exponential function far away from the origin by only knowing its value in a countable set of points near the origin. By using this perspective, one can extend the idea of superoscillations to functions that are not a sum of exponential functions, namely to the notion of supershift. The study …

Escalating Hydrological Extremes And Whiplashes In The Western U.S.: Challenges For Water Management And Frontline Communities, Wenzhao Li, Surendra Maharjan, Joshua B. Fisher, Thomas Piechota, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Western U.S. is experiencing significant changes in its hydrological dynamics, marked by increased variability and rapid “whiplash” shifts between extreme drought and flood conditions. This study quantified these changes using a customized hydrological water year index, which correlated better with surface water storage in the basins than other drought/wetness indicators. Application of the index revealed heightened hydrological extremes and whiplash events post-2015 in all Western U.S. basins, with nearly 72% of stations facing critically dry conditions in 2021 and over 54% experiencing extreme wet conditions in 2023. Future projections indicate a decline of 8.5%–13.2% in non-extreme water year types …

Sustainability Planning For Waste Management In Midwestern Small Suburban Cities, Karen Frances Goodwin

Walden Dissertations and Doctoral Studies

Sustainability planning in small suburban cities, particularly as it relates to waste management programs, remains an underexplored area in scholarly research. Without long-term planning, these cities often react to issues in a fragmented manner rather than implementing proactive policies, negatively affecting public health and well-being. The purpose of this study was to examine sustainable waste management policy processes that enable sustainability planning in Midwestern small suburban cities. Using Jones et al.’s local adaptive capacity framework and Q-methodology, viewpoint patterns were analyzed to understand what motivates decision-makers to foster an environment conducive to sustainability planning. Thirty-one participants representing three local government …

Memory-Augmented Llm Agent For Predicting Locomotion Modes In Construction Activities, Ehsan Ahmadi

LSU Doctoral Dissertations

The construction industry faces significant challenges, including labor shortages, high physical demands, and safety risks, necessitating advanced assistive technologies like exoskeletons to enhance worker efficiency and reduce injuries. However, effective exoskeleton control in dynamic construction environments requires accurate locomotion prediction, a task complicated by the diversity of activities and reliance on supervised learning methods that struggle to generalize. This study investigates a multimodal approach to locomotion prediction, leveraging speech commands and visual data from smart glasses to enable adaptive and safe human-exoskeleton interaction. The research unfolds in two stages: the first develops a framework to evaluate the zero-shot capability and …

Proceedings Of The 12th Research Symposium At Mammoth Cave National Park, Pat Kambesis Editor, Lee Anne Bledsoe Editor, Ana K. Celis Editor

Mammoth Cave Research Symposia

Proceedings of the 12th Research Symposium at Mammoth Cave National Park: Celebrating 100 Years of Scientific Research & Resource Management in the Mammoh Cave Region.

Design Of Silicon Grating Metasurfaces For Beam Deflecting In Solid-State Light Detecting And Ranging (Lidar), Matthew Baker

Honors Program Theses and Projects

My thesis begins with an overview of LiDAR (Light Detecting and Ranging) and theory for electromagnetic wave propagation. We establish problems that arise from the use of external beam steering components in LiDAR systems. As a possible solution, we introduce the concept of a metasurface with sub-wavelength dimensions. Grating metasurfaces utilize periodicity to change the phase gradient along a surface. Using a row of posts on a substrate, we can confine light towards one side of a structure, deflecting at angles towards a maximum angle determined by the structure’s geometry. These metasurfaces are small enough to be directly incorporated onto …

System Administration Practices And Experimentation, Nicholas Z. Young

Honors Program Theses and Projects

This undergraduate departmental honors capstone project experiments with and demonstrates System Administration practices that are used in enterprise environments. The skills and practices of System Administrators are crucial to maintain large-scale IT infrastructure. This project aimed to gain a deeper, practical understanding of the role of a System Administrator in an emulated environment. Through hands-on experimentation, this project addressed the responsibilities of a System Administrator, such as controlling user access, adding hardware, automating tasks, monitoring systems, overseeing and developing a backup strategy, maintaining local documentation, and security practices. This project demonstrated some of the complexities that lie in each of …

Computational Thinking, Informal Learning, And Makerspace, Redar Ismail

College of Computing and Digital Media Dissertations

The continuous advancement of technology has made it a crucial tool across various disciplines. As adaptation to this rapidly progressing field occurred, teaching and learning problem-solving skills are more essential than ever for empowering individuals to succeed across diverse fields. Studies have shown that engaging K-12 students in activities encouraging science, technology, engineering, mathematics (STEM), and computational thinking (CT) are critical for teaching them how to deal with complex problems (Rode, Barkhuus, & Ioannou, 2024; Shu & Huang, 2021). Makerspaces and making activities became popular among researchers and educators due to their potential to advance learning, enhance problem-solving skills, and …

Modeling Molten Lithium Carbonate As Pollutant Absorbing Agent, Lucian G. Forestieri

Student Summer Scholars Manuscripts

Coal burning generates gaseous pollutants that are toxic to local environments and human health, namely hydrochloric acid and sulfur dioxide ( HCl and SO₂). Current methods for capturing these pollutants are flue gas desulfurization, which utilize solid or water- dissolved carbonates. This method, however, is inefficient mainly due to the product salts blocking further reactions. Molten carbonates may be a more efficient alternative. Experimental work cannot observe these reaction mechanisms, and the small number of current computational models do not match experimental properties. This work aims to develop a computational model of gaseous HCl scattering off the surface …

Remotely Sensed High-Resolution Soil Moisture And Evapotranspiration: Bridging The Gap Between Science And Society, Jingyi Huang, Vinit Sehgal, Laura V. Alvarez, Luca Brocca, Shuohao Cai, Rui Cheng, Xinghua Cheng, Jinyang Du, Bassil El Masri, K. Arthur Endsley, Yilin Fang, Jie Hu, Mahesh Jampani, Md Golam Kibria, Gerbrand Koren, Lingcheng Li, Laibao Liu, Jiafu Mao, Hernan A. Moreno, Angela Rigden, Mingjie Shi, Xiaoying Shi, Yaoping Wang, Xi Zhang, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

This paper reviews the current state of high-resolution remotely sensed soil moisture (SM) and evapotranspiration (ET) products and modeling, and the coupling relationship between SM and ET. SM downscaling approaches for satellite passive microwave products leverage advances in artificial intelligence and high-resolution remote sensing using visible, near-infrared, thermal-infrared, and synthetic aperture radar sensors. Remotely sensed ET continues to advance in spatiotemporal resolutions from MODIS to ECOSTRESS to Hydrosat and beyond. These advances enable a new understanding of bio-geo-physical controls and coupled feedback mechanisms between SM and ET reflecting the land cover and land use at field scale (3–30 m, daily). …

Real-World Implementation Of A Noninvasive, Ai-Augmented, Anemia-Screening Smartphone App And Personalization For Hemoglobin Level Self-Monitoring, Robert G. Mannino, Julie Sullivan, Jennifer K. Frediani, Paul George, Jeremy Whitson, James Tumlin, L. Andrew Lyon, Erika A. Tyburski, Wilbur A. Lam

Engineering Faculty Articles and Research

Anemia, characterized by low blood hemoglobin (Hgb) levels, afflicts >2 billion individuals worldwide. Here, we report real-world data generated by a smartphone app that noninvasively screens for anemia using only “fingernail selfies.” App data for anemia screening were obtained from >1.4 million uses across the United States enabling geographic mapping of Hgb levels. Of those, 9,061 users also self-reported complete blood count Hgb levels for comparison, resulting in accuracy and performance that match gold standard laboratory testing and a sensitivity and specificity of 89% and 93%, respectively, when using an anemia cutoff of 12.5 g/dL. Geotagged data enabled construction of …

Integrating Artificial Intelligence In Orthopedic Care: Advancements In Bone Care And Future Directions, Rahul Kumar, Kyle Sporn, Joshua Ong, Ethan Waisberg, Phani Paladugu, Swapna Vaja, Tamer Hage, Tejas C. Sekhar, Amar S. Vadhera, Alex Ngo, Nasif Zaman, Alireza Tavakkoli, Mouayad Masalkhi

SKMC Student Presentations and Publications

Artificial intelligence (AI) is revolutionizing the field of orthopedic bioengineering by increasing diagnostic accuracy and surgical precision and improving patient outcomes. This review highlights using AI for orthopedics in preoperative planning, intraoperative robotics, smart implants, and bone regeneration. AI-powered imaging, automated 3D anatomical modeling, and robotic-assisted surgery have dramatically changed orthopedic practices. AI has improved surgical planning by enhancing complex image interpretation and providing augmented reality guidance to create highly accurate surgical strategies. Intraoperatively, robotic-assisted surgeries enhance accuracy and reduce human error while minimizing invasiveness. AI-powered smart implant sensors allow for in vivo monitoring, early complication detection, and individualized rehabilitation. …

Quasi-Normal Modes Of Extended Uncertainty Principle Kerr Black Holes, Ava Hoeger, Jonas Mureika

Honors Thesis

The current understanding of gravity is shaped largely by Albert Einstein’s theory of General Relativity. This theory is highly successful at predicting phenomenon on macroscopic scales, but it faces unphysical singularities at quantum scales. This thesis will explore the possibility of combining General Relativity with quantum mechanics through the Extended Uncertainty Principle (EUP), which provides a new, fundamental length scale correction to the Heisenberg Uncertainty Principle. This allows for quantum gravity effects at macroscopic scales, which will be examined through Kerr black holes with event horizons on the order of . These black holes are rotating and electrically neutral, and …

Efficient Eeg Epilepsy Classification And Feature Selections Based On Hellinger Distance, Muhammed Sadiq

Theses and Dissertations

Accurate and efficient detection of epileptic seizures from EEG signals remains a critical challenge due to high-dimensional data, class imbalance, and the limitations of standard classifiers. This thesis introduces two novel models to address these challenges. The first model presents a new classifier based on the Hellinger Distance, specifically designed to enhance discriminative capability and robustness against imbalanced datasets. By integrating the Hellinger Distance Classifier with Particle Swarm Optimization (PSO) for feature selection, this model significantly improves classification performance while reducing computational complexity. Experimental evaluations on the Bonn dataset demonstrate an accuracy of 96.25%, an F1-score of 97.74%, a recall …

Probing Binding And Allosteric Mechanisms Of The Kras Interactions With Monobodies And Affimer Proteins : Ensemble-Based Mutational Profiling And Thermodynamic Analysis Of Binding Energetics And Allostery Reveal Diversity Of Functional Hotspots And Cryptic Pockets Linked By Conserved Communication Network, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Guang Hu, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

KRAS, a historically "undruggable" oncogenic driver, has eluded targeted therapies due to its lack of accessible binding pockets in its active state. This study investigates the conformational dynamics, binding mechanisms, and allosteric communication networks of KRAS in complexes with monobodies (12D1, 12D5) and affimer proteins (K6, K3, K69) to characterize the binding and allosteric mechanisms and hotspots of KRAS binding. Through molecular dynamics simulations, mutational scanning, binding free energy analysis and network-based analyses, we identified conserved allosteric hotspots that serve as critical nodes for long-range communication in KRAS. Key residues in β-strand 4 (F78, L80, F82), α-helix 3 (I93, H95, …

Climate Constrains The Enhancement Of Co2 Fertilization On Forest Gross Primary Productivity, Xinyuan Wei, Daniel J. Hayes, Christopher R. Schwalm, Joshua B. Fisher, Deborah N. Huntzinger, Lei Ma, Rodrigo Vargas, Nathaniel A. Brunsell

Mathematics, Physics, and Computer Science Faculty Articles and Research

Forest gross primary production (GPP) is influenced by the interplay between climate conditions and atmospheric CO₂ levels, which interact in complex ways, generating both compensating and amplifying effects. In this study, eddy covariance flux measurements from 50 forest ecosystems were integrated with simulations from 14 terrestrial biosphere models to investigate how climate conditions and atmospheric CO₂ concentrations regulate forest GPP. This approach bridges site-level observations with biome-scale model estimates to develop a global understanding. Our findings suggest that in boreal and cold temperate regions, temperature primarily constrains the enhancement of the CO₂ fertilization on forest GPP; however, …