Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Faculty Publications

Discipline
Institution
Keyword
Publication Year
File Type

Articles 961 - 990 of 9043

Full-Text Articles in Entire DC Network

Flood Risk Assessment For Residences At The Neighborhood Scale By Owner/Occupant Type And First-Floor Height, Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland, Md Adilur Rahim, Robert V. Rohli Jan 2023

Flood Risk Assessment For Residences At The Neighborhood Scale By Owner/Occupant Type And First-Floor Height, Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland, Md Adilur Rahim, Robert V. Rohli

Faculty Publications

Evaluating flood risk is an essential component of understanding and increasing community resilience. A robust approach for quantifying flood risk in terms of average annual loss (AAL) in dollars across multiple homes is needed to provide valuable information for stakeholder decision-making. This research develops a computational framework to evaluate AAL at the neighborhood level by owner/occupant type (i.e., homeowner, landlord, and tenant) for increasing first-floor height (FFH). The AAL values were calculated here by numerically integrating loss-exceedance probability distributions to represent economic annual flood risk to the building, contents, and use. A simple case study for a census block in …

Go to article

How Good Is A Tactical-Grade Gnss + Ins (Mems And Fog) In A 20-M Bathymetric Survey?, Johnson O. Oguntuase, Anand Hiroji, Peter Komolafe Jan 2023

How Good Is A Tactical-Grade Gnss + Ins (Mems And Fog) In A 20-M Bathymetric Survey?, Johnson O. Oguntuase, Anand Hiroji, Peter Komolafe

Faculty Publications

This paper examines how tactical-grade Inertial Navigation Systems (INS), aided by Global Navigation Satellite System (GNSS) modules, vary from a survey-grade system in the bath-ymetric mapping in depths less than 20 m. The motivation stems from the advancements in sensor developments, measurement processing algorithms, and the proliferation of autonomous and uncrewed surface vehicles often seeking to use tactical-grade systems for high-quality bathymetric products. While the performance of survey-grade GNSS + INS is well-known to the hydrographic and marine science community, the performance and limitations of the tactical-grade micro-electro-mechanical system (MEMS) and tactical-grade fiber-optic-gyro (FOG) INS aided with GNSS require some …

Go to article

Exploring Barriers To The Adoption Of Internet Of Things-Based Precision Agriculture Practices, Gaganpreet Singh Hundal, Chad Laux, Dennis R. Buckmaster, Mathias J. Sutton, Michael Langemeier Jan 2023

Exploring Barriers To The Adoption Of Internet Of Things-Based Precision Agriculture Practices, Gaganpreet Singh Hundal, Chad Laux, Dennis R. Buckmaster, Mathias J. Sutton, Michael Langemeier

Faculty Publications

The production of row crops in the Midwestern (Indiana) region of the US has been facing environmental and economic sustainability issues. There has been an increase in trend for the application of fertilizers (nitrogen & phosphorus), farm machinery fuel costs and decreasing labor productivity leading to non-optimized usage of farm inputs. Literature describes how sustainable practices such as profitability (return on investments), operational cost reduction, hazardous waste reduction, delivery performance and overall productivity might be adopted in the context of precision agriculture technologies (variable rate irrigation, variable rate fertilization, cloud-based analytics, and telematics for farm machinery navigation). The literature review …

Go to article

Deep Transfer Learning For Approximate Model Predictive Control, Samuel Arce Munoz, Junho Park, Cristina M. Stewart, Adam M. Martin, John Hedengren Jan 2023

Deep Transfer Learning For Approximate Model Predictive Control, Samuel Arce Munoz, Junho Park, Cristina M. Stewart, Adam M. Martin, John Hedengren

Faculty Publications

Transfer learning is a machine learning technique that takes a pre-trained model that has already been trained on a related task, and adapts it for use on a new, related task. This is particularly useful in the context of model predictive control (MPC), where deep transfer learning is used to improve the training of the MPC by leveraging the knowledge gained from related controllers. One way in which transfer learning is applied in the context of MPC is by using a pre-trained deep learning model of the MPC, and then fine-tuning the controller training for a new process automation task. …

Go to article

Data Augmentation For Neutron Spectrum Unfolding With Neural Networks, James Mcgreivy, Juan J. Manfredi, Daniel Siefman Jan 2023

Data Augmentation For Neutron Spectrum Unfolding With Neural Networks, James Mcgreivy, Juan J. Manfredi, Daniel Siefman

Faculty Publications

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and …

Go to article

Data Visualization Of Big Data For Predictive And Descriptive Analytics For Stroke, Covid-19, And Diabetes, Richard S. Segall, Soichiro Takashashi Jan 2023

Data Visualization Of Big Data For Predictive And Descriptive Analytics For Stroke, Covid-19, And Diabetes, Richard S. Segall, Soichiro Takashashi

Faculty Publications

Visualization of big data is crucial for meaningful interpretations and especially for healthcare. Brief discussions are made for big data, background for healthcare, and recent work in big data analytics for healthcare. This research pertains to different levels of big data: 5,110 vs. 101,766 vs. 320,200 vs. 1 million data values. Data visualizations and predictive analytics are presented of big data for selected diseases of stroke with 5,110 data values, diabetes with 101,766 data values, and two COVID-19 studies: one with 320,200 data values and another with 1 million data values. Data visualizations are generated for these diseases with big …

Go to article

Drivers Of Diatom Production And The Legacy Of Eutrophication In Two River Plume Regions Of The Northern Gulf Of Mexico, Jeffrey W. Krause, Adam D. Boyette, Israel A. Marquez, Rebecca A. Pickering, Kanchan Maiti Jan 2023

Drivers Of Diatom Production And The Legacy Of Eutrophication In Two River Plume Regions Of The Northern Gulf Of Mexico, Jeffrey W. Krause, Adam D. Boyette, Israel A. Marquez, Rebecca A. Pickering, Kanchan Maiti

Faculty Publications

In the northern Gulf of Mexico (nGoM), the Louisiana Shelf (LS) and Mississippi Bight (MB) subregions are influenced by eutrophication to varying degrees. Despite recognition that dissolved silicon may regulate diatom productivity in the nGoM, there is only one published data set reporting biogenic silica (bSiO2) production rates for each subregion. We report that bSiO2 production rates on the LS and MB are high and appear to be controlled by different nutrients among seasons. Despite exceptional upper trophic level biomass regionally, which suggests significant primary production by diatoms (as in other systems), gross euphotic-zone integrated bSiO2 production rates are lower …

Go to article

Dissolved Organic Carbon Dynamics And Fluxes In Mississippi-Atchafalaya Deltaic System Impacted By An Extreme Flood Event And Hurricanes: A Multi-Satellite Approach Using Sentinel-2/3 And Landsat-8/9 Data, Bingqing Liu, Eurico J. D’Sa, Francesca Messina, Melissa M. Baustian, Kanchan Maiti, Victor H. Rivera-Monroy, Wei Huang, Ioannis Y. Georgiou Jan 2023

Dissolved Organic Carbon Dynamics And Fluxes In Mississippi-Atchafalaya Deltaic System Impacted By An Extreme Flood Event And Hurricanes: A Multi-Satellite Approach Using Sentinel-2/3 And Landsat-8/9 Data, Bingqing Liu, Eurico J. D’Sa, Francesca Messina, Melissa M. Baustian, Kanchan Maiti, Victor H. Rivera-Monroy, Wei Huang, Ioannis Y. Georgiou

Faculty Publications

Transport of riverine and wetland-derived dissolved organic carbon (DOC) spanning tidal wetlands, estuaries, and continental shelf waters functionally connects terrestrial and aquatic carbon reservoirs, yet the magnitude and ecological significance of this variable and its spatiotemporal linkage remains uncertain for coastal deltaic regions, such as Mississippi River Delta Plain, which includes Mississippi (MR) and Atchafalaya (AR) rivers and estuaries with vast expanses of wetlands and coastal forests. We examined DOC dynamics and fluxes in this large river-dominated wetland-estuarine system for the period between 2019 and 2021 that included an extreme river flood event in 2019, two major hurricanes (Barry in …

Go to article

Design And Field-Scale Demonstration Of The Buoyant-Kill Process For Restoring Integrity Of Wells With Sustained Casing Pressure, Efecan Demirci, Andrew Wojtanowicz Jan 2023

Design And Field-Scale Demonstration Of The Buoyant-Kill Process For Restoring Integrity Of Wells With Sustained Casing Pressure, Efecan Demirci, Andrew Wojtanowicz

Faculty Publications

Sustained Casing Pressure (SCP) is the persistent casinghead pressure resulting from the well’s annular integrity loss and migration of gas above the leaking cement sheath. Downhole—intervention methods for SCP removal employ workover rigs to access and plug off the leaking annulus at depth from within the well. The inexpensive rig-less method of Buoyant Kill involves surface injection of immiscible heavy fluid at the casinghead into the well’s annulus to replace the annular fluid column above the gas-leaking cement and stop gas migration. Laboratory and pilot-size testing have shown feasibility of the method. Presented here, is a field-scale demonstration experiment conducted …

Go to article

Lighting Energy Load Prediction Framework Using Agent-Based Simulation And Artificial Neural Network Models, Sorena Vosoughkhosravi, Seddigheh Norouziasl, Amirhosein Jafari Jan 2023

Lighting Energy Load Prediction Framework Using Agent-Based Simulation And Artificial Neural Network Models, Sorena Vosoughkhosravi, Seddigheh Norouziasl, Amirhosein Jafari

Faculty Publications

Lighting is responsible for 17% of the total electricity consumption in commercial buildings in the United States. Investigating the lighting energy load provides the potential for more energy-saving in commercial buildings. Nonetheless, the development of lighting load prediction models has received limited attention in extant literature. This study proposes a framework to predict the lighting schedule and load in office buildings by integrating an agent-based model into an artificial neural network model. A small office building is used as a case study to simulate lighting load based on occupancy information using an agent-based model. Then, an artificial neural network model …

Go to article

Aerostructural Predictions Combining Fenics And A Viscous Vortex Particle Method, Ryan Anderson, Andrew Ning, Ru Xiang, Sebastiaan P. C. Van Schie, Mark Sperry, Darshan Sarojini, David Kamensky, John T. Hwang Jan 2023

Aerostructural Predictions Combining Fenics And A Viscous Vortex Particle Method, Ryan Anderson, Andrew Ning, Ru Xiang, Sebastiaan P. C. Van Schie, Mark Sperry, Darshan Sarojini, David Kamensky, John T. Hwang

Faculty Publications

Electric Vertical Takeoff and Landing (eVTOL) aircraft experience complex, unsteady aerodynamic interactions between rotors, wings, and fuselage that can make design difficult. We introduce a new framework for predicting aerostructural interactions. Specifically, we demonstrate the coupling of a finite element solver with Reissner-Mindlin shell theory for computing deflections and a viscous vortex particle for capturing wakes. We perform convergence studies of the aerodynamics and the coupled aerostructural model. Finally, we share some preliminary results of the dynamic aeroelastic response of Uber’s eCRM-002 main wing, and share some qualitative observations.

Go to article

Understanding The Role Of Online Teaching Assistants In Student Engagement, Sara H. Tuiloma, Charles R. Graham Jan 2023

Understanding The Role Of Online Teaching Assistants In Student Engagement, Sara H. Tuiloma, Charles R. Graham

Faculty Publications

In this paper, we examine how online teaching assistants (OLTAs) interact with students in terms of affective, behavioral, and cognitive support and the influence of OLTA training on these interactions. Through a thematic network analysis, using a tracking instrument and semi-structured interviews with 10 OLTAs, we examined how online university students are supported based on the quantity and quality of interactions with OLTAs, and how training contributes to interactions. Our research addressed two key questions: (1) How do OLTAs support learners in the quantity and quality of interactions? and (2) How does OLTA training around affective and behavioral support influence …

Go to article

Preliminary Findings From A Collaborative Storytelling Program On Life Participation And Communication Among Persons With Aphasia, Bijoyaa Mohapatra, Ranjini Mohan Jan 2023

Preliminary Findings From A Collaborative Storytelling Program On Life Participation And Communication Among Persons With Aphasia, Bijoyaa Mohapatra, Ranjini Mohan

Faculty Publications

Aims: The purpose of this study is to evaluate the outcomes of a remotely delivered collaborative storytelling program based on the TimeslipsTM approach in persons with aphasia (PWA). The program aims to improve social interaction, communication, and participation through a guided experience. Methods: Six PWA of mild-moderate severity and of fluent and nonfluent types participated in the program twice a week for seven weeks. They collaboratively created 28 free-form stories from staged pictures. PWA were tested pre- and post-treatment on several validated outcome measures representing each of the Living with Aphasia: Framework for Outcome Measurement (A-FROM) domains. PWA self-rated on …

Go to article

Mmst-Vit: Climate Change-Aware Crop Yield Prediction Via Multi-Modal Spatial-Temporal Vision Transformer, Fudong Lin, Summer Crawford, Kaleb Guillot, Yihe Zhang, Yan Chen, Xu Yuan, Li Chen, Shelby Williams, Robert Minvielle, Xiangming Xiao, Drew Gholson, Nicolas Ashwell, Tri Setiyono, Brenda Tubana, Lu Peng, Magdy Bayoumi, Nian Feng Tzeng Jan 2023

Mmst-Vit: Climate Change-Aware Crop Yield Prediction Via Multi-Modal Spatial-Temporal Vision Transformer, Fudong Lin, Summer Crawford, Kaleb Guillot, Yihe Zhang, Yan Chen, Xu Yuan, Li Chen, Shelby Williams, Robert Minvielle, Xiangming Xiao, Drew Gholson, Nicolas Ashwell, Tri Setiyono, Brenda Tubana, Lu Peng, Magdy Bayoumi, Nian Feng Tzeng

Faculty Publications

Precise crop yield prediction provides valuable information for agricultural planning and decision-making processes. However, timely predicting crop yields remains challenging as crop growth is sensitive to growing season weather variation and climate change. In this work, we develop a deep learning-based solution, namely Multi-Modal Spatial-Temporal Vision Transformer (MMST-ViT), for predicting crop yields at the county level across the United States, by considering the effects of short-term meteorological variations during the growing season and the long-term climate change on crops. Specifically, our MMST-ViT consists of a Multi-Modal Transformer, a Spatial Transformer, and a Temporal Transformer. The Multi-Modal Transformer leverages both visual …

Go to article

Wooing “Willing Dupes”: The Bush Administration’S Use Of Emotional Language In The Drive Toward War With Iraq, Michael F. Russo Jan 2023

Wooing “Willing Dupes”: The Bush Administration’S Use Of Emotional Language In The Drive Toward War With Iraq, Michael F. Russo

Faculty Publications

The publicly available texts of the George W. Bush administration from September 11, 2001, to March 19, 2003, as presented in The Public Papers of the Presidents of the United States, were analyzed for word frequency and the words themselves analyzed for emotional weight using the NRC Emotion Intensity Lexicon. Transcripts of six television news agencies (ABC, CBS, NBC, CNN, FOX, and PBS) were also analyzed for word frequency to determine the extent to which these agencies may have repeated and consequently amplified the rhetoric of the administration. Public opinion polling for this same period was examined in an …

Go to article

Gene-Educational Attainment Interactions In A Multi-Population Genome-Wide Meta-Analysis Identify Novel Lipid Loci, Lisa De Las Fuentes, Karen L. Schwander, Michael R. Brown, Amy R. Bentley, Thomas W. Winkler, Yun Ju Sung, Patricia B. Munroe, Clint L. Miller, Hugo Aschard, Stella Aslibekyan, Traci M. Bartz, Lawrence F. Bielak, Jin Fang Chai, Ching Yu Cheng, Rajkumar Dorajoo, Mary F. Feitosa, Xiuqing Guo, Fernando P. Hartwig, Andrea Horimoto, Ivana Kolčić, Elise Lim, Yongmei Liu, Alisa K. Manning, Jonathan Marten, Solomon K. Musani, Raymond Noordam, Sandosh Padmanabhan, Tuomo Rankinen, Melissa A. Richard, Paul M. Ridker, Albert V. Smith, Dina Vojinovic, Alan B. Zonderman Jan 2023

Gene-Educational Attainment Interactions In A Multi-Population Genome-Wide Meta-Analysis Identify Novel Lipid Loci, Lisa De Las Fuentes, Karen L. Schwander, Michael R. Brown, Amy R. Bentley, Thomas W. Winkler, Yun Ju Sung, Patricia B. Munroe, Clint L. Miller, Hugo Aschard, Stella Aslibekyan, Traci M. Bartz, Lawrence F. Bielak, Jin Fang Chai, Ching Yu Cheng, Rajkumar Dorajoo, Mary F. Feitosa, Xiuqing Guo, Fernando P. Hartwig, Andrea Horimoto, Ivana Kolčić, Elise Lim, Yongmei Liu, Alisa K. Manning, Jonathan Marten, Solomon K. Musani, Raymond Noordam, Sandosh Padmanabhan, Tuomo Rankinen, Melissa A. Richard, Paul M. Ridker, Albert V. Smith, Dina Vojinovic, Alan B. Zonderman

Faculty Publications

Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: “Some College” (yes/no, for any education beyond high school) and “Graduated College” (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10−8) and suggestive (p < 1 × 10−6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

Go to article

Charting The Course To Advance Dei In The Ocean Sciences A Case Study, Christopher F. D’Elia, Katherine Falls, Sibel Bargu, Linda Hooper-Bùi Jan 2023

Charting The Course To Advance Dei In The Ocean Sciences A Case Study, Christopher F. D’Elia, Katherine Falls, Sibel Bargu, Linda Hooper-Bùi

Faculty Publications

The Louisiana State University College of the Coast & Environment (LSU CC&E) developed a multi-faceted strategic initiative to increase its diversity, equity, and inclusion. Elements of this initiative began one-by-one over the last decade and were aggregated into a comprehensive implementation plan—the 2020 CC&E Diversity, Equity, and Inclusion Action Plan. Based on best practices in the “physical sciences” (i.e., geosciences, including oceanography), the plan aims to augment recruitment and retention using limited resources and personnel. The long-range goal is to increase the number of PhD graduates from underrepresented groups by employing strategies that start at the 6–12th grade level. The …

Go to article

Quasistatic Evolution With Unstable Forces, Debdeep Bhattacharya, Robert P. Lipton Jan 2023

Quasistatic Evolution With Unstable Forces, Debdeep Bhattacharya, Robert P. Lipton

Faculty Publications

We consider load controlled quasistatic evolution. Well posedness results for the nonlocal continuum model related to peridynamics are established. We show local existence and uniqueness of quasistatic evolution for load paths originating at stable critical points. These points can be associated with local energy minima among the convex set of deformations belonging to the strength domain of the material. The evolution of the displacements, however, is not constrained to lie inside the strength domain of the material. The load-controlled evolution is shown to exhibit energy balance.

Go to article

Simulating Grain Shape Effects And Damage In Granular Media Using Peridem, Debdeep Bhattacharya, Robert P. Lipton Jan 2023

Simulating Grain Shape Effects And Damage In Granular Media Using Peridem, Debdeep Bhattacharya, Robert P. Lipton

Faculty Publications

We provide a numerical platform for the analysis of particle shape and topology effect on the macroscopic behavior of granular media. We work within a discrete element method (DEM) framework and apply a peridynamic model for deformable particles accounting for deformation and damage of individual particles. To accommodate arbitrary particle shapes including nonconvex ones as well as particle topology, an efficient method is developed to keep intraparticle peridynamic interaction within particle boundaries. Particle contact with the rigid boundary wall is computed analytically to improve accuracy. To speed up simulations with particles of different shapes and sizes the initial configuration is …

Go to article

Local Observer For Parameters And For State Variables Of Nonlinear Systems, Frederic Mazenc, Michael Malisoff Jan 2023

Local Observer For Parameters And For State Variables Of Nonlinear Systems, Frederic Mazenc, Michael Malisoff

Faculty Publications

We provide new observer designs to simultaneously identify parameters and states of systems whose nonlinearities have order two near the origin, which include cubic terms arising in the study of jump phenomena, process control, and bistable models of aerospace systems. This yields local exponential convergence of the state estimation error to zero, basin of attraction estimates, and fixed time parameter identification. We illustrate our result using Duffing's equation, whose cubic term puts it outside the scope of prior methods.

Go to article

Discrete-Time Trajectory-Based Stabilization Approach Using Interval Observer, Frederic Mazenc, Michael Malisoff, Jackson Knox Jan 2023

Discrete-Time Trajectory-Based Stabilization Approach Using Interval Observer, Frederic Mazenc, Michael Malisoff, Jackson Knox

Faculty Publications

We provide a discrete-time vector valued analog of recently developed continuous-time trajectory-based estimates. We use it to provide a discrete-time version of Halanay's inequality. We combine the results with interval observers to prove exponential stability properties for discrete-time linear systems with uncertainties whose arbitrarily long input delays are compensated for by reduction model controls, and a robust global exponential stability result for observers for discrete-time linear systems.

Go to article

Reference Governor Design In The Presence Of Uncertain Polynomial Constraints, Rick Schieni, Chengwei Zhao, Michael Malisoff, Laurent Burlion Jan 2023

Reference Governor Design In The Presence Of Uncertain Polynomial Constraints, Rick Schieni, Chengwei Zhao, Michael Malisoff, Laurent Burlion

Faculty Publications

Reference governors are add-on schemes that are used to modify trajectories to prevent controlled dynamical systems from violating input or state constraints, and so are playing an increasingly important role in aerospace, robotic, and other applications. Here we present a novel reference governor design for systems whose polynomial constraints depend on unknown bounded parameters. This is a significant departure from earlier treatments of reference governors, where the constraints were linear or known, because here we transfer the uncertainties into the constraints instead of having them in the closed loop dynamics, which greatly simplifies the task of determining future evolution of …

Go to article

Almost Fixed Time Observers For Parameters And For State Variables Of Nonlinear Systems, Frederic Mazenc, Michael Malisoff, Laurent Burlion Jan 2023

Almost Fixed Time Observers For Parameters And For State Variables Of Nonlinear Systems, Frederic Mazenc, Michael Malisoff, Laurent Burlion

Faculty Publications

We provide new finite-time and fast-converging observers for continuous-time nonlinear systems that contain unknown constant parameters and measurement delays. When the dynamics are affine in the unmeasured state, we obtain fixed time observers that identify unknown states and unknown model parameters. When the dynamics contain a nonlinearity that depends on the unmeasured state, we instead obtain asymptotic convergence of our observers, whose rate of convergence converges to infinity as the growth rate of this nonlinearity converges to zero, so in this case we call the observers almost fixed time observers. Our examples illustrate how our assumptions can be easily checked.

Go to article

Mathematical Models Of Topologically Protected Transport In Twisted Bilayer Graphene, Guillaume Bal, Paul Cazeaux, Daniel Massatt, Solomon Quinn Jan 2023

Mathematical Models Of Topologically Protected Transport In Twisted Bilayer Graphene, Guillaume Bal, Paul Cazeaux, Daniel Massatt, Solomon Quinn

Faculty Publications

Twisted bilayer graphene gives rise to large moir\'e patterns that form a triangular network upon mechanical relaxation. If gating is included, each triangular region has gapped electronic Dirac points that behave as bulk topological insulators with topological indices depending on valley index and the type of stacking. Since each triangle has two oppositely charged valleys, they remain topologically trivial. In this work, we address several questions related to the edge currents of this system by analysis and computation of continuum PDE models. First, we derive the bulk invariants corresponding to a single valley, and then apply a bulk-interface correspondence to …

Go to article

Uniqueness Of Entire Solutions To Quasilinear Equations Of P-Laplace Type, Nguyen Cong Phuc, Igor E. Verbitsky Jan 2023

Uniqueness Of Entire Solutions To Quasilinear Equations Of P-Laplace Type, Nguyen Cong Phuc, Igor E. Verbitsky

Faculty Publications

We prove the uniqueness property for a class of entire solutions to the equation (Formula presented) where σ is a nonnegative locally finite measure in Rn, absolutely continuous with respect to the p-capacity, and div A(x, ∇u) is the A-Laplace operator, under standard growth and monotonicity assumptions of order p (1 < p < ∞) on A(x, ξ) (x, ξ ∈ Rn); the model case A(x, ξ) = ξ|ξ|p−2 corresponds to the p-Laplace operator ∆p on Rn. Our main results establish uniqueness of solutions to a similar problem,(Formula presented) in the sub-natural growth case 0 < q < p − 1, where µ, σ are nonnegative locally finite measures in Rn, absolutely continuous with respect to the …

Go to article

An Upper Bound For The Circumference Of A 3-Connected Binary Matroid, Manoel Lemos, James Oxley Jan 2023

An Upper Bound For The Circumference Of A 3-Connected Binary Matroid, Manoel Lemos, James Oxley

Faculty Publications

Jim Geelen and Peter Nelson proved that, for a loopless connected binary ma-troid M with an odd circuit, if a largest odd circuit of M has k elements, then a largest circuit of M has at most 2k − 2 elements. The goal of this note is to show that, when M is 3-connected, either M has a spanning circuit, or a largest circuit of M has at most 2k − 4 elements. Moreover, the latter holds when M is regular of rank at least four.

Go to article

Generalizing Cographs To 2-Cographs, James Oxley, Jagdeep Singh Jan 2023

Generalizing Cographs To 2-Cographs, James Oxley, Jagdeep Singh

Faculty Publications

A graph in which every connected induced subgraph has a disconnected complement is called a cograph. Such graphs are precisely the graphs that do not have the 4-vertex path as an induced subgraph. We define a 2-cograph to be a graph in which the complement of every 2-connected induced subgraph is not 2-connected. We show that, like cographs, 2-cographs can be recursively defined and are closed under induced minors. We characterize the class of non-2-cographs for which every proper induced minor is a 2-cograph. We further find the finitely many members of this class whose complements are also induced-minor-minimal non-2-cographs.

Go to article

The Lagrangian Numerical Relativity Code Sphincs_Bssn_V1.0, Stephan Rosswog, Francesco Torsello, Peter Diener Jan 2023

The Lagrangian Numerical Relativity Code Sphincs_Bssn_V1.0, Stephan Rosswog, Francesco Torsello, Peter Diener

Faculty Publications

We present version 1.0 of our Lagrangian numerical relativity code SPHINCS_BSSN. This code evolves the full set of Einstein equations, but contrary to other numerical relativity codes, it evolves the matter fluid via Lagrangian particles in the framework of a high-accuracy version of smooth particle hydrodynamics (SPH). The major new elements introduced here are: (i) a new method to map the stress–energy tensor (known at the particles) to the spacetime mesh, based on a local regression estimate; (ii) additional measures that ensure the robust evolution of a neutron star through its collapse to a black hole; and (iii) further refinements …

Go to article

A Finite Element Method For A Two-Dimensional Pucci Equation, Susanne C. Brenner, Li Yeng Sung, Zhiyu Tan Jan 2023

A Finite Element Method For A Two-Dimensional Pucci Equation, Susanne C. Brenner, Li Yeng Sung, Zhiyu Tan

Faculty Publications

A nonlinear least-squares finite element method for strong solutions of the Dirichlet boundary value problem of a two-dimensional Pucci equation on convex polygonal domains is investigated in this paper. We obtain a priori and a posteriori error estimates and present corroborating numerical results, where the discrete nonsmooth and nonlinear optimization problems are solved by an active set method and an alternating direction method with multipliers.

Go to article

An Interior Maximum Norm Error Estimate For The Symmetric Interior Penalty Method On Planar Polygonal Domains, Susanne C. Brenner, Li Yeng Sung Jan 2023

An Interior Maximum Norm Error Estimate For The Symmetric Interior Penalty Method On Planar Polygonal Domains, Susanne C. Brenner, Li Yeng Sung

Faculty Publications

We establish an interior maximum norm error estimate for the symmetric interior penalty method on planar polygonal domains.

Go to article

First Prev Next Last