More Like this

1. How Anti-Social Personality Traits and Anti-Establishment Views Promote Beliefs in Election Fraud, QAnon, and COVID-19 Conspiracy Theories and Misinformation

   https://doi.org/10.1177/1532673X221139434  

   Enders, Adam; Klofstad, Casey; Stoler, Justin; Uscinski, Joseph_E (November 2022, American Politics Research)

   Conspiracy theories and misinformation (CTM) became a salient feature of the Trump era. However, traditional explanations of political attitudes and behaviors inadequately account for beliefs in CTM or the deleterious behaviors they are associated with. Here, we integrate disparate literatures to explain beliefs in CTM regarding COVID-19, QAnon, and voter fraud. We aim to provide a more holistic accounting, and to determine which political, psychological, and social factors are most associated with such beliefs. Using a unique national survey, we find that anti-social personality traits, anti-establishment orientations, and support for Donald Trump are more strongly related to beliefs in CTM than traditional left-right orientations or other frequently posited factors, such as education, science literacy, and social media use. Our findings encourage researchers to move beyond the traditional correlates of political behavior when examining beliefs that express anti-social tendencies or a deep skepticism of social and political institutions. 

   more » « less
2. A Continuous Threshold Model of Cascade Dynamics

   https://doi.org/10.1109/CDC40024.2019.9029844  

   Zhong, Yaofeng Desmond; Leonard, Naomi Ehrich (December 2019, IEEE Conference on Decisions and Control)

   null (Ed.)

   We present a continuous threshold model (CTM) of cascade dynamics for a network of agents with real-valued activity levels that change continuously in time. The model generalizes the linear threshold model (LTM) from the literature, where an agent becomes active (adopts an innovation) if the fraction of its neighbors that are active is above a threshold. With the CTM we study the influence on cascades of heterogeneity in thresholds for a network comprised of a chain of three clusters of agents, each distinguished by a different threshold. The system is most sensitive to change as the dynamics pass through a bifurcation point: if the bifurcation is supercritical the response will be contained, while if the bifurcation is subcritical the response will be a cascade. We show that there is a subcritical bifurcation, thus a cascade, in response to an innovation if there is a large enough disparity between the thresholds of sufficiently large clusters on either end of the chain; otherwise the response will be contained. 

   more » « less
3. PWA-CTM: An Extended Cell-Transmission Model based on Piecewise Affine Approximation of the Fundamental Diagram

   https://doi.org/10.1109/MED54222.2022.9837131  

   Alimardani, Fatemeh; Baras, John S. (June 2022, Proceedings of the 30th Mediterranean Conference on Control and Automation (MED 2022))

   Throughout the past decades, many different versions of the widely used first-order Cell-Transmission Model (CTM) have been proposed for optimal traffic control. Highway traffic management techniques such as Ramp Metering (RM) are typically designed based on an optimization problem with nonlinear constraints originating in the flow-density relation of the Fundamental Diagram (FD). Most of the extended CTM versions are based on the trapezoidal approximation of the flow-density relation of the Fundamental Diagram (FD) in an attempt to simplify the optimization problem. However, this relation is naturally nonlinear, and crude approximations can greatly impact the efficiency of the optimization solution. In this study, we propose a class of extended CTMs that are based on piecewise affine approximations of the flow-density relation such that (a) the integrated squared error with respect to the true relation is greatly reduced in comparison to the trapezoidal approximation, and (b) the optimization problem remains tractable for real-time application of ramp metering optimal controllers. A two-step identification method is used to approximate the FD with piecewise affine functions resulting in what we refer to as PWA-CTMs. The proposed models are evaluated by the performance of the optimal ramp metering controllers, e.g. using the widely used PI-ALINEA approach, in complex highway traffic networks. Simulation results show that the optimization problems based on the PWA-CTMs require less computation time compared to other CTM extensions while achieving higher accuracy of the flow and density evolution. Hence, the proposed PWA-CTMs constitute one of the best approximation approaches for first-order traffic flow models that can be used in more general and challenging modeling and control applications. 

   more » « less
4. Performance Projection of a High-Temperature CO ₂ Transport Membrane Reactor for Combined CO ₂ Capture and Methane-to-Ethylene Conversion

   https://doi.org/10.1149/1945-7111/ac6ae7  

   Li, Xin; Huang, Kevin; Van Dam, Noah; Jin, Xinfang (May 2022, Journal of The Electrochemical Society)

   Direct conversion of methane into ethylene through the oxidative coupling of methane (OCM) is a technically important reaction. However, conventional co-fed fixed-bed OCM reactors still face serious challenges in conversion and selectivity. In this paper, we apply a finite element model to simulate OCM reaction in a plug-flow CO₂/O₂transport membrane (CTM) reactor with a directly captured CO₂and O₂mixture as a soft oxidizer. The CTM is made of three phases: molten carbonate, 20% Sm-doped CeO₂, and LiNiO₂. The membrane parameters are first validated by CO₂/O₂flux data obtained from CTM experiments. The OCM reaction is then simulated along the length of tubular plug-flow reactors filled with a La₂O₃-CaO-modified CeO₂catalyst bed, while a mixture of CO₂/O₂is gradually added through the wall of the tubular membrane. A 12-step OCM kinetic mechanism is considered in the model for the catalyst bed and validated by data obtained from a co-fed fixed-bed reactor. The modeled results indicate a much-improved OCM performance by membrane reactor in terms of C₂-yield and CH₄conversion rate over the state-of-the-art, co-fed, fixed-bed reactor. The model further reveals that improved performance is fundamentally rooted in the gradual methane conversion with CO₂/O₂offered by the plug-flow membrane reactor. 

   more » « less
5. Fast Chip Transient Temperature Simulation via Machine Learning

   https://doi.org/10.1109/MLCAD65511.2025.11189189  

   Hajikhodaverdian, Mohammadamin; Reda, Sherief; Coskun, Ayse K (September 2025, IEEE)

   With growing transistor densities, analyzing temperature in 2D and 3D integrated circuits (ICs) is becoming more complicated and critical. Finite-element solvers give accurate results, but a single transient run can take hours or even days. Compact thermal models (CTMs) shorten the temperature simulation running time using a numerical solver based on the duality between thermal and electric properties. However, CTM solvers often still take hours for small-scale chips because of iterative numerical solvers. Recent work using machine learning (ML) models creates a fast and reliable framework for predicting temperature. However, current ML models demand large input samples and hours of GPU training to reach acceptable accuracy. To overcome the challenges stated, we design an ML framework that couples with CTMs to accelerate steady-state and transient thermal analysis without large data inputs. Our framework combines principal-component analysis (PCA) with closed-form linear regression to predict the on-chip temperature directly. The linear regression weights are solved analytically, so training for a grid size of 512 × 512 finishes in under a minute with only 15–20 CTM samples. Experimental results show that our framework can achieve more than 33x and 49.6x speedup for steady-state and transient simulation of a chip with a 245.95mm^2 footprint, keeping the mean squared error below 0.1 deg C^2 . 

   more » « less