arXiv subjects

Fan Lei

Publications and source records attributed to Fan Lei.

13 recordsLinked to original sources

arXiv2026

The Impact of Uncertainty Visualization on Trust in Thematic Maps

Thematic maps are widely used to communicate spatial patterns to non-expert audiences. Although uncertainty is inherent in thematic map data, it is rarely visualized, raising questions about how its inclusion affects trust. Prior work offers mixed perspectives: some argue that uncertainty fosters trust through transparency, while others suggest it may reduce trust by introducing confusion. Yet few empirical studies explicitly measure trust in thematic maps. We conducted a between-subjects experiment (N=161) to evaluate how visualizing uncertainty at varying levels (low, medium, high) influences trust. We find that uncertainty visualization generally reduces trust, with greater reductions observed as uncertainty levels increase. However, maps dominated by low uncertainty do not significantly differ in trust from those with no uncertainty. Moreover, while uncertainty visualization tends to make readers question the accuracy of the data, it appears to have a weaker influence on perceptions of the mapmaker's integrity.

cs.HC↗

arXiv2025

Skeptik: A Hybrid Framework for Combating Potential Misinformation in Journalism

The proliferation of misinformation in journalism, often stemming from flawed reasoning and logical fallacies, poses significant challenges to public understanding and trust in news media. Traditional fact-checking methods, while valuable, are insufficient for detecting the subtle logical inconsistencies that can mislead readers within seemingly factual content. To address this gap, we introduce Skeptik, a hybrid framework that integrates Large Language Models (LLMs) with heuristic approaches to analyze and annotate potential logical fallacies and reasoning errors in online news articles. Operating as a web browser extension, Skeptik automatically highlights sentences that may contain logical fallacies, provides detailed explanations, and offers multi-layered interventions to help readers critically assess the information presented. The system is designed to be extensible, accommodating a wide range of fallacy types and adapting to evolving misinformation tactics. Through comprehensive case studies, quantitative analyses, usability experiments, and expert evaluations, we demonstrate the effectiveness of Skeptik in enhancing readers' critical examination of news content and promoting media literacy. Our contributions include the development of an expandable classification system for logical fallacies, the innovative integration of LLMs for real-time analysis and annotation, and the creation of an interactive user interface that fosters user engagement and close reading. By emphasizing the logical integrity of textual content rather than relying solely on factual accuracy, Skeptik offers a comprehensive solution to combat potential misinformation in journalism. Ultimately, our framework aims to improve critical reading and protect the public from deceptive information online and enhance the overall credibility of news media.

cs.HC↗

arXiv2025

MapIQ: Evaluating Multimodal Large Language Models for Map Question Answering

Recent advancements in multimodal large language models (MLLMs) have driven researchers to explore how well these models read data visualizations, e.g., bar charts, scatter plots. More recently, attention has shifted to visual question answering with maps (Map-VQA). However, Map-VQA research has primarily focused on choropleth maps, which cover only a limited range of thematic categories and visual analytical tasks. To address these gaps, we introduce MapIQ, a benchmark dataset comprising 14,706 question-answer pairs across three map types: choropleth maps, cartograms, and proportional symbol maps spanning topics from six distinct themes (e.g., housing, crime). We evaluate multiple MLLMs using six visual analytical tasks, comparing their performance against one another and a human baseline. An additional experiment examining the impact of map design changes (e.g., altered color schemes, modified legend designs, and removal of map elements) provides insights into the robustness and sensitivity of MLLMs, their reliance on internal geographic knowledge, and potential avenues for improving Map-VQA performance.

cs.CL↗

arXiv2025

Background in Low Earth Orbiting Cherenkov Detectors, and Mitigation Strategies

Cherenkov detectors have been used in space missions for many decades, and for a variety of purposes, including for example, for Galactic Cosmic Ray (GCR) and Solar Energetic Particle (SEP) measurements. Cherenkov detectors are sensitive to many types of particles that are present in the environment of space, including gamma rays, trapped particles and cosmic particles, and each particle component acts as essentially a background when trying to view another specific particle component. In this research, GRAS/Geant4 simulations were performed to characterise the count rates that a simple Cherenkov detector design would experience in a low Earth orbit, and we find that Cherenkov count rates due to most particle components vary significantly depending on many different factors, including the location in the orbit, the date of the orbit, whether or not the detector is within the van Allen belts, and whether or not a solar particle event is occurring. We find that a small Cherenkov detector is readily able to gather detailed data on both trapped particles and spectral information during Ground-Level Enhancements. We also investigate the use of coincidence as a method to remove count rates due to trapped particles and delta electrons, finding that this method is generally very effective for resolving count rates due to GLEs amongst intense trapped particle environments, but that some Cherenkov count rates due to trapped particles are still observed in the simulated south Atlantic anomaly region.

physics.ins-det↗

arXiv2025

FEWSim: A Visual Analytic Framework for Exploring the Nexus of Food-Energy-Water Simulations

The interdependencies of food, energy, and water (FEW) systems create a nexus opportunity to explore the strengths and vulnerabilities of individual and cross-sector interactions within FEW systems. However, the variables quantifying nexus interactions are hard to observe, which hinders the cross-sector analysis. To overcome such challenges, we present FEWSim, a visual analytics framework designed to support domain experts in exploring and interpreting simulation results from a coupled FEW model. FEWSim employs a three-layer asynchronous architecture: the model layer integrates food, energy, and water models to simulate the FEW nexus; the middleware layer manages scenario configuration and execution; and the visualization layer provides interactive visual exploration of simulated time-series results across FEW sectors. The visualization layer further facilitates the exploration across multiple scenarios and evaluates scenario differences in performance using sustainability indices of the FEW nexus. We demonstrate the utility of FEWSim through a case study for the Phoenix Active Management Area (AMA) in Arizona.

cs.HC↗

arXiv2024

Reconstructing 3D Flow from 2D Data with Diffusion Transformer

Fluid flow is a widely applied physical problem, crucial in various fields. Due to the highly nonlinear and chaotic nature of fluids, analyzing fluid-related problems is exceptionally challenging. Computational fluid dynamics (CFD) is the best tool for this analysis but involves significant computational resources, especially for 3D simulations, which are slow and resource-intensive. In experimental fluid dynamics, PIV cost increases with dimensionality. Reconstructing 3D flow fields from 2D PIV data could reduce costs and expand application scenarios. Here, We propose a Diffusion Transformer-based method for reconstructing 3D flow fields from 2D flow data. By embedding the positional information of 2D planes into the model, we enable the reconstruction of 3D flow fields from any combination of 2D slices, enhancing flexibility. We replace global attention with window and plane attention to reduce computational costs associated with higher dimensions without compromising performance. Our experiments demonstrate that our model can efficiently and accurately reconstruct 3D flow fields from 2D data, producing realistic results.

cs.CE↗

arXiv2024

Photoelectron superlubricity

Superlubricity, a state where friction between two contact surfaces is nearly zero, has a great potential to revolutionize various mechanical systems by significantly reducing energy dissipation and enhancing efficiency. It can be realized either by structural incommensurate contact between crystalline surfaces or by creating highly passive interfaces to cancel out the adhesive forces. However, fabricating and maintaining such superlubric surfaces still present challenges, often disabled by surface structural defects or susceptibility to humid atmospheres, which renders superlubricity fragile. Here, we propose a novel strategy of photoelectron superlubricity (PESL), where robust superlubricity can be achieved in humid atmospheres by in-situ laser-irradiating the contact interface of an amorphous carbon film sliding against sapphire ball. We demonstrate that PESL not only exhibits a high resistance to environmental disturbances but also features rapid response. The formation of PESL originates from the laser-irradiating induced formation of nanographene-layered interface and enrichment of photoelectrons at the interface, resulting in a repulsive electric field between the nanographene layers. The discovery of PESL opens a new avenue for achieving superlubricity, and also provides novel insights for smart friction, mechanical motion control and light manipulation.

cond-mat.mes-hall↗

arXiv2024

AniMAIRE -- A New Openly Available Tool for Calculating Atmospheric Ionising Radiation Dose Rates and Single Event Effects During Anisotropic Conditions

AniMAIRE (Anisotropic Model for Atmospheric Ionising Radiation Effects) is a new model and Python toolkit for calculating radiation dose rates experienced by aircraft during anisotropic solar energetic particle events. AniMAIRE expands the physics of the MAIRE+ model such that dose rate calculations can be performed for anisotropic solar energetic particle conditions by supplying a proton or alpha particle rigidity spectrum, a pitch angle distribution, and the conditions of Earth's magnetosphere. In this paper, we describe the algorithm and top-level structure of AniMAIRE and showcase AniMAIRE's capabilities by analysing the dose rate maps that AniMAIRE produces when the time-dependent spectra and pitch angle distribution for GLE71 are inputted. We find that the dose rates AniMAIRE produces for the event fall between the dose rates produced by the WASAVIES and CRAC:DOMO models. Dose rate maps that evolve throughout the event are also shown, and it is found that each peak in the inputted pitch angle distribution generates a dose rate hotspot in each of the polar regions. AniMAIRE has been made available openly online so that it can be downloaded and run freely on local machines and so that the space weather community can easily contribute to it using Github forking.

physics.app-ph↗

arXiv2024

Understanding Reader Takeaways in Thematic Maps Under Varying Text, Detail, and Spatial Autocorrelation

Maps are crucial in conveying geospatial data in diverse contexts such as news and scientific reports. This research, utilizing thematic maps, probes deeper into the underexplored intersection of text framing and map types in influencing map interpretation. In this work, we conducted experiments to evaluate how textual detail and semantic content variations affect the quality of insights derived from map examination. We also explored the influence of explanatory annotations across different map types (e.g., choropleth, hexbin, isarithmic), base map details, and changing levels of spatial autocorrelation in the data. From two online experiments with $N=103$ participants, we found that annotations, their specific attributes, and map type used to present the data significantly shape the quality of takeaways. Notably, we found that the effectiveness of annotations hinges on their contextual integration. These findings offer valuable guidance to the visualization community for crafting impactful thematic geospatial representations.

cs.HC↗

arXiv2023

GeoLinter: A Linting Framework for Choropleth Maps

Visualization linting is a proven effective tool in assisting users to follow established visualization guidelines. Despite its success, visualization linting for choropleth maps, one of the most popular visualizations on the internet, has yet to be investigated. In this paper, we present GeoLinter, a linting framework for choropleth maps that assists in creating accurate and robust maps. Based on a set of design guidelines and metrics drawing upon a collection of best practices from the cartographic literature, GeoLinter detects potentially suboptimal design decisions and provides further recommendations on design improvement with explanations at each step of the design process. We perform a validation study to evaluate the proposed framework's functionality with respect to identifying and fixing errors and apply its results to improve the robustness of GeoLinter. Finally, we demonstrate the effectiveness of the GeoLinter - validated through empirical studies - by applying it to a series of case studies using real-world datasets.

cs.HC↗

arXiv2023

GeoExplainer: A Visual Analytics Framework for Spatial Modeling Contextualization and Report Generation

Geographic regression models of various descriptions are often applied to identify patterns and anomalies in the determinants of spatially distributed observations. These types of analyses focus on answering why questions about underlying spatial phenomena, e.g., why is crime higher in this locale, why do children in one school district outperform those in another, etc.? Answers to these questions require explanations of the model structure, the choice of parameters, and contextualization of the findings with respect to their geographic context. This is particularly true for local forms of regression models which are focused on the role of locational context in determining human behavior. In this paper, we present GeoExplainer, a visual analytics framework designed to support analysts in creating explanative documentation that summarizes and contextualizes their spatial analyses. As analysts create their spatial models, our framework flags potential issues with model parameter selections, utilizes template-based text generation to summarize model outputs, and links with external knowledge repositories to provide annotations that help to explain the model results. As analysts explore the model results, all visualizations and annotations can be captured in an interactive report generation widget. We demonstrate our framework using a case study modeling the determinants of voting in the 2016 US Presidential Election.

cs.HC↗

arXiv2022

The Variation of Radiation Effective Dose Rates and Single Event Effect Rates at Aviation Altitudes with Magnetospheric Conditions and Geographic Location

The geographic structure of radiation dose rates at aircraft altitudes in Earth's atmosphere during the irradiation of Earth by proton spectra from incoming solar particle events is examined using the recently developed MAIRE+ software. Conditions are examined under two incoming proton spectra, a low/hard spectral index and a high/soft spectral index spectra, which are representative of some of the solar particle events that have caused reasonably sized Ground-Level Enhancements/Events (GLEs) over the past 70 years. It is found through the use of `cut-throughs' of the atmosphere, that the atmosphere can be divided into three volumes; a high dose rate polar region, a low dose rate equatorial region, and a transition region between the two. The location of these regions as a function of latitude, longitude and altitude is characterised. It is also found that the location of the transition region changes for different magnetospheric disturbance levels, implying that the total radiation dose rate an aircraft will experience if it passes through the transition region will be subject to large systematic uncertainties, particularly during the currently unknown levels of magnetospheric disturbance that a major solar event could cause. The impact that various magnetospheric conditions might have on dose rates that specific flight routes might experience is also discussed.

physics.app-ph↗

arXiv2017

Geant4 simulations of soft proton scattering in X-ray optics. A tentative validation using laboratory measurements

Low energy protons (< 300 keV) can enter the field of view of X-ray space telescopes, scatter at small incident angles, and deposit energy on the detector, causing intense background flares at the focal plane or in the most extreme cases, damaging the X-ray detector. A correct modelization of the physics process responsible for the grazing angle scattering processes is mandatory to evaluate the impact of such events on the performance of future X-ray telescopes as the ESA ATHENA mission. For the first time the Remizovich model, in the approximation of no energy losses, is implemented top of the Geant4 release 10.2. Both the new scattering physics and the built-in Coulomb scattering are used to reproduce the latest experimental results on grazing angle proton scattering. At 250 keV multiple scattering delivers large proton angles and it is not consistent with the observation. Among the tested models, the single scattering seems to better reproduce the scattering efficiency at the three energies but energy loss obtained at small scattering angles is significantly lower than the experimental values. In general, the energy losses obtained in the experiment are higher than what obtained by the simulation. The experimental data are not completely representative of the soft proton scattering experienced by current X-ray telescopes because of the lack of measurements at low energies (< 200 keV) and small reflection angles, so we are not able to address any of the tested models as the one that can certainly reproduce the scattering behavior of low energy protons expected for the ATHENA mission. We can, however, discard multiple scattering as the model able to reproduce soft proton funneling, and affirm that Coulomb single scattering can represent, until further measurements, the best approximation of the proton scattered angular distribution at the exit of X-ray optics.

astro-ph.IM↗