Digital Commons Network^™

Codec-M: The Multi-Lingual Manosphere Subcorpus Of The Corpus Of Digital Extremism And Conspiracies, Rachel Mccullough, Daniel Drylie, Mindl Barta, Cass Dykeman, Daniel Smith

English Faculty Publications

In 2023, the U.S. Surgeon General warned the public of the current “loneliness epidemic” and its potential consequences on physical and mental health. One possible consequence of this epidemic is the growth of a movement defined by loneliness and isolation: the incel (“involuntary celibate”) movement. This warning presents a worrying glimpse at the future, as the incel movement, along with other parts of the manosphere, is one that espouses violently misogynist rhetoric which is intrinsically linked to right-wing extremism. While linguistic studies have been conducted on the speech of incels and other constituent movements of the manosphere, few of these …

A Comparison Of Microcrystal Electron Diffraction And X-Ray Powder Diffraction For The Structural Analysis Of Metal-Organic Frameworks, Erik Biehler, Silvana Pagola, Daniel Stam, Johannes Merkelbach, Christian Jandl, Tarek M. Abdel-Fattah

Chemistry & Biochemistry Faculty Publications

This study successfully implemented microcrystal electron diffraction (microED) and X-ray powder diffraction (XRPD) for the crystal structure determination of a new phase, TAF-CNU-1, Ni(C₈H₄O₄)·3H₂O, solved by microED from single microcrystals in the powder and refined at the kinematic and dynamic electron diffraction theory levels. This nickel metal–organic framework (MOF), together with its cobalt and manganese analogues with formula M (C₈H₄O₄)·2H₂O with M = Mn ^II or Co^II, were synthesized in aqueous media as one-pot preparations from the corresponding hydrated metal chlorides and sodium terephthalate, as a promising `green' synthetic route to moisture-stable MOFs. The crystal structures of the …

Extended Inter-Laboratory Characterization Of The New Coastal Seawater Dissolved Organic Matter Reference Material Trm-0522, Alexander J. Craig, Lydia Babcock-Adams, Maxime C. Bridoux, Charlotte Brun, Juliana D'Andrilli, Aleksandar I. Goranov, Patrick G. Hatcher, Oliver Lechtenfeld, Hang Li, Rebecca Matos, Garrett Mckay, Amy M. Mckenna, Madelyn Miller, Sasha Wagner, Margot E. White, Alexander Zherebker, Jeffrey A. Hawkes

Chemistry & Biochemistry Faculty Publications

Dissolved organic matter (DOM) reference materials are critical to ensuring reliable comparability of measurements across experiments and between labs. TRM-0522, isolated in 2022 from 45 m deep seawater off of Sweden’s west coast, fills the niche of a previously unavailable coastal marine DOM reference material. After its isolation, we detailed a limited number of metrics for TRM-0522, initially disclosing Orbitrap high-resolution mass spectrometry, nuclear magnetic resonance, carbon proportion, absorbance, and fluorescence data. With TRM-0522 becoming more widely used, a variety of labs have generated different metrics that help to characterize and define the chemical properties of this coastal reference material. …

Metathesis Or Isomerization: Counteranion Directed Reactivity Of Grubbs I, Paul D. Miller, Joe B. Calkins, Craig A. Bayse, Trandon A. Bender

Chemistry & Biochemistry Faculty Publications

Catalytic isomerization of alkenes has garnered interest for many years, but there are remaining challenges when it comes to thermodynamic selectivity and uncontrolled isomerization. Nonbiased substrates, be it sterically or thermodynamically, remain challenging for many catalysts, with a few examples available in the more modern literature. Herein, we present the controlled isomerization of linear alkenes with a cocatalytic mixture of commercially available catalyst and reagents: Grubbs I, tris(pentafluorophenyl)borane, and triethylsilane. DFT calculations indicate that an observed alkylidyne hydride intermediate is in rapid equilibrium with an alkylidene that binds the alkene substrate. This combination results in a pi-acidic metal and a …

Stack Bonding In Pentacene And Its Derivatives, Craig A. Bayse

Chemistry & Biochemistry Faculty Publications

Understanding the nature of π-stacking interactions is important to molecular recognition, self-assembly, and organic semiconductors. The stack bonding order (SBO) model of π-stacking has shown that the conformations of dimers occur when the combinations of monomer MOs are overall stack bonding in character. DFT calculations show that minima found on the potential energy surface for the π-stacked dimers of pentacene and perfluoropentacene occur when the dimer MOs are constructed from combinations of monomer MOs with an allowed SBO. An ex-amination of the MOs of π-stacked dimers extracted from X-ray structures of alkynyl derivatives like TIPS-pentacene pack at one or more …

Application Of Telc Model To Better Elucidate Neural Stimulation By Touch, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

Aim: This study is to better understand how the transient ion transport activity of touch receptors could change the graded potential to stimulate an action potential firing.

Methods: The latest transmembrane-electrostatically localized protons/cations charges (TELC) theory is employed for numerical analysis to calculate the neural touch signal transduction responding time required to fire an action potential spike.

Results: A neural action potential spike was constructed successfully using newly developed time-dependent TELC-based neural transmembrane potential integral equations (Equations 5, 6, and 7). The results explicated that the TELC curve has an inverse relationship with neural transmembrane potential since its curve appears …

Identification Of Π-Stacking Motifs In Naphthalene Diimides Via Solid-State Nmr, Jennifer E. Mejia, Hannah E. Butler-Au, Nalaya E. Thompson, Karcher D. Goodman, Elizabeth R. Zengel, Robert D. Pike, Jingdong Mao, Craig A. Bayse

Chemistry & Biochemistry Faculty Publications

Organic electronics, featuring π-conjugated small molecules and polymers, have gained significant attention for their potential in flexible, lightweight devices. However, characterization of the ordered, π-stacking domains within these materials using microscopy or X-ray diffraction (XRD) is challenging with complex systems or when crystallography is impractical. This study applied 1D ¹³C multiple cross-polarization magic angle spinning (multiCP/MAS) and 2D ¹H-¹³C heteronuclear correlation (HetCor) solid-state nuclear magnetic resonance (ssNMR) to systematically characterize π-stacking motifs in a series of N,N'-dialkyl naphthalene diimides (NDIs). These techniques were shown to distinguish between the electronic environments attributed to different π-stacking motifs adopted in these NDIs, such …

Assemblage Structure Of Large Carnivorous Coral Reef Fishes At Shallow And Mesophotic Depths In Two Of The Largest And Most Isolated Marine Protected Areas In The Philippines, Rene A. Abesamis, Mikaela L. Salvador, Ryan Murray, Kymry Delijero, Segundo F. Conales, Jean T. Utzurrum, Christopher E. Bird, David T. Gauthier

Biological Sciences Faculty Publications

Overfishing remains a threat to coral reef fishes globally, with large carnivores often the most vulnerable. Marine protected areas (MPAs) can restore fish populations and biodiversity, but their impact has been understudied in mesophotic coral ecosystems (MCEs – extensions of shallow reefs from 30 to 150 m). We analyzed baited remote underwater videos recorded in 2016 to investigate the assemblage structure of large carnivorous fishes at shallow (4–12 m) and mesophotic (45–96 m) depths in two of the largest and most isolated MPAs in the Philippines: Tubbataha Reefs Natural Park (TRNP), a fully no-take MPA enacted in 1988; and Cagayancillo, …

Emerging Nanotechnology Approaches For Blood Disorders: A Comprehensive Review Of Nano-Hematinics And Plant-Based Nanomedicines, Hassan Abdulsalam Adewuyi, Khairat Shamsudeen, Fatima Mahmoud Muhammad, Adeola Kolawole Victor, Sakariyau Adio Waheed, Adepeju Matilda Adekoya, Kashim Ibrahim Muhammad, Blessing Temitayo Longe, Abdulgaffar Abdulquddus

Chemistry & Biochemistry Faculty Publications

Background: Disorders affecting blood components, such as anemia, coagulopathies, and hematologic malignancies, continue to pose significant global health burdens. Traditional therapies often fall short due to adverse effects, limited bioavailability, and insufficient targeting of disease sites.

Objective: This review synthesizes current advances in nano-hematinics and plant-based nanomedicines (phyto-nanomedicines) as innovative strategies for managing blood-related conditions. These nanoscale interventions are designed to enhance therapeutic precision, bioactivity, and safety.

Methods: A systematic review was conducted using major scientific databases including PubMed, Scopus, Web of Science, and ScienceDirect. Search terms were carefully selected to retrieve literature published between 2015 and 2024 that discussed …

Amphiphilic Tripodal Metalloligands: Synthesis, Coordination Chemistry And Preliminary Catalysis, Austin W. Medley, Paul D. Miller, Craig A. Bayse, Robert D. Pike, Trandon A. Bender

Chemistry & Biochemistry Faculty Publications

Triscatecholate binding has been widely studied in the context of biological systems, supramolecular chemistry, and weak aggregate interactions. However, the utilization of the triscatecholate binding motif for the preparation of metalloligands remains unexplored. Herein, we report the synthesis, structural characterization, and functional studies of a triscatecholate ligand with an appended pyridyl residue as a candidate for such applications. Our findings reveal that the selective formation of cis-triscatecholate-based metalloligands is influenced by electronic effects on the catecholate anions, enabling the targeted synthesis of Al(III), Ga(III), and In(III) triscatecholate metalloligands capable of binding Zn(II) and Ru(II) at the appended pyridyl moiety for …

Laser-Induced Graphene Sensor For The Electrochemical Detection Of Acetaminophen, Abdellatif Ait Lahcen, Mazhar Sher, Sikander Ameer, Gymama Slaughter

Center for Bioelectronics Publications

Here we present a simple and efficient method for fabricating laser-induced graphene (LIG) electrodes for the electrochemical detection of acetaminophen (AAP), a crucial analgesic and antipyretic that can become toxic at elevated concentrations. Unlike conventional sensors that require intricate chemical modifications, the fabricated LIG-based sensor eliminates the need for functionalization, offering a streamlined sensing solution. The LIG electrodes were characterized using scanning electron microscopy, energy-dispersive spectroscopy, and Raman spectroscopy, which confirmed the formation of a highly porous graphene network with excellent purity and conductivity. Cyclic voltammetry analysis with a ferricyanide redox probe revealed a large electroactive surface area of 1.21 …

Coastal Flooding And Housing Market Liquidity: Policy Implications For Eastern U. S. Communities, Wai Yan Siu, Rex Sitti

ODU Articles

Coastal flooding poses an escalating threat to communities across the U.S East Coast, where rising sea levels and intensifying storms increasingly overwhelm existing infrastructure and natural defenses. These events generate complex economic consequences that extend beyond immediate property damage to affect community stability and long-term development patterns. The real estate industry in particular, faces increasing levels of flood risk. Existing research on climate risk and real estate markets focuses predominantly on price capitalization effects, overlooking the critical dimension of housing market liquidity. This study examines the causal impact of coastal flooding on days-on-market (DOM), a metric of liquidity in the …

Electrical Homeostasis Of The Inner Mitochondrial Membrane Potential, Peyman Fahimi, Lázaro A. M. Castanedo, P. Thomas Vernier, Cherif F. Matta

Bioelectrics Publications

The electric potential across the inner mitochondrial membrane must be maintained within certain bounds for the proper functioning of the cell. A feedback control mechanism for the homeostasis of this membrane potential is proposed whereby an increase in the electric field decreases the rate-limiting steps of the electron transport chain (ETC). An increase in trans-membrane electric field limits the rate of proton pumping to the inter-membrane gap by slowing the ETC reactions and by intrinsically induced electroporation that depolarizes the inner membrane. The proposed feedback mechanism is akin to a Le Chatelier's-type principle of trans-membrane potential feedback control.

Analysing Nontraditional Students' Chatgpt Interaction, Engagement, Self-Efficacy And Performance: A Mixed-Methods Approach, Mohan Yang, Shiyan Jiang, Belle Li, Kristin Herman, Tian Luo, Shanan Chappell Moots, Nolan Lovett

STEMPS Faculty Publications

Generative artificial intelligence brings opportunities and unique challenges to nontraditional higher education students, stemming, in part, from the experience of the digital divide. Providing access and practice is critical to bridge this divide and equip students with needed digital competencies. This mixed-methods study investigated how nontraditional higher education students interact with ChatGPT in multiple courses and examined relationships between ChatGPT interactions, engagement, self-efficacy and performance. Data were collected from 73 undergraduate and graduate students through chat logs, course reflections and artefacts, surveys and interviews. ChatGPT interactions were analysed using four metrics: prompt number, depth of knowledge (DoK), prompt relevance and …

Utilizing Artificial Intelligence As A Strategic Risk Management Tool For Public Sector Operations And Auditing Processes, Oğuz Ümit Tamer, Bruce D. Mcdonald Iii, Farouk Hemici, Georgia Kontogeorga

School of Public Service Faculty Publications

Symbolizing a significant turning point in the historical landscape, AI is becoming an effective tool in today's public administration, not only for increasing capacity, quality, and speed in services, but also for strategic risk management. Regulators and algorithmic auditing play a central role in implementing fairness, transparency, and persistent controls against risks in AI systems. Discussing modern applications of AI, such as anomaly-based fraud detection, resource estimation, and continuous auditing, and their respective strengths and weaknesses, this study concludes that AI significantly enhances efficiency and oversight but also poses the risk of enshrining bias, opacity, and accountability gaps. By considering …

Engagement In Practice: Partnering With Communities To Address Nuisance Flooding Challenges, Carol L. Considine, Mujde Erten-Unal, Dalya Ismael, Luka Alandra Hamal-Serenity, Farzaneh Soflaei

Engineering Technology Faculty Publications

Many communities are already experiencing the impacts of climate change that disrupt their daily lives. In Coastal Virginia, these impacts take the form of nuisance and stormwater flooding caused by sea level rise and changes in precipitation. Coastal Virginia has one of the highest relative sea level rise rates on the Atlantic Coast and the regional planning district commission recommends that Atlas 14 rainfall intensity, duration, and frequency curves be increased by 20% to account for changes in rainfall. The Coastal Community Design Collaborative (CCDC), a partnership between Hampton University Architecture and Old Dominion University Engineering & Technology, has had …

Leveraging Transformer-Based Ocr Model With Generative Data Augmentation For Engineering Document Recognition, Wael Khallouli, Mohammad Shahab Uddin, Andres Sousa-Poza, Jiang Li, Samuel Kovacic

Engineering Management & Systems Engineering Faculty Publications

The long-standing practice of document-based engineering has resulted in the accumulation of a large number of engineering documents across various industries. Engineering documents, such as 2D drawings, continue to play a significant role in exchanging information and sharing knowledge across multiple engineering processes. However, these documents are often stored in non-digitized formats, such as paper and portable document format (PDF) files, making automation difficult. As digital engineering transforms processes in many industries, digitizing engineering documents presents a crucial challenge that requires advanced methods. This research addresses the problem of automatically extracting textual content from non-digitized legacy engineering documents. We introduced …

Obesity Prediction From Structural Mri Using Conformal Deep Learning With Uncertainty Quantification, W. Farzana, A. G. A. Temtam, B. Humud-Arboleda, L. Ma, M. Bean, F. Gerard Moeller, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Obesity arises from a neurobehavioral disorder in which the brain’s regulation of hunger and food intake is impaired, leading to an imbalance between energy consumption and expenditure. One key phenotype associated with obesity is body mass index (BMI). BMI is influenced by multiple causal pathways driven by behavioral, metabolic, and genetic factors. Traditional obesity prediction studies often rely on magnetic resonance imaging (MRI) voxel-based morphometry to correlate BMI with obesity-related clinical measurements and brain structure, predominantly gray matter volume (GMV). However, the altered brain regions are variable and widespread between studies, with some literature presenting contradictory results between BMI and …

Personalized Prediction Of Tumor Recurrence With Image-Guided Physics-Informed Computational Model In High-Grade Gliomas, Walia Farzana, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

High grade gliomas are infiltrating tumors characterized by their diffusive invasion and proliferative growth. Across and within patients heterogeneity of tumors makes it challenging to determine tumor spatial extent after surgical resection. Traditionally, tumor growth predictions after surgical resections rely on generalized models and population-based observations, which do not account for individual patient differences. To address this gap, we propose a personalized approach with image-guided computational model (digital twin) that incorporates physics-based modeling to predict tumor recurrence. Our digital twin involves an inverse modeling step, followed by a recurrence model that accounts for varying surgical effects. The physics-guided inverse model …

Biomedical Mxene-Polymer Nanocomposites: Advancing Photothermal Therapy, Antibacterial Action, And Smart Drug Delivery: A Review, Ali Mohammad Amani, Lobat Tayebi, Ehsan Vafa, Mohammad Javad Azizli, Milad Abbasi, Ahmad Vaez, Hesam Kamyab, Daniel Simancas-Racines, Shreeshivadasan Chelliapan

Electrical & Computer Engineering Faculty Publications

MXenes are hydrophilic, conductive, tunable, and biocompatible two-dimensional ceramic materials prepared by etching the 'A' layer from their precursor MAX phases. Although MXenes show exceptional promise in photothermal therapy, biosensing, and regenerative medicine, they face challenges such as oxidative instability in physiological environments, limited drug-loading capacity, and unpredictable immune responses. To address these limitations, MXene/polymer nanocomposites incorporating both synthetic polymers (e.g., polyethylene glycol (PEG), polyvinyl alcohol (PVA), polyvinylpyrrolidone (PVP), and polylactic-co-glycolic acid (PLGA)) and natural biopolymers (e.g., cellulose nanofiber, gelatin, chitosan, hyaluronic acid, and soybean phospholipids) have been developed. These composites enhance functionality for biomedical applications such as photothermal cancer …

Optimizing Superconducting Nb Film Cavities By Mitigating Medium-Field Q-Slope Through Annealing, B. Abdisatarov, G. Eremeev, H. E. Elsayed-Ali, D. Bafia, A. Murthy, Z. Sung, A. Netepenko, A. Romanenko, C. P.A. Carlos, G. J. Rosaz, S. Calatroni, S. Leith, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are of interest in applications in various superconducting devices, such as superconducting radiofrequency cavities for particle accelerators and superconducting qubits for quantum computing. In this study, we address the persistent medium-field Q-slope issue in Nb film cavities, which, despite their high-quality factor at low RF fields, exhibit a significant Q-slope at medium RF fields compared to bulk Nb cavities. Traditional heat treatments, effective in reducing surface resistance and mitigating the Q-slope in bulk Nb cavities, are challenging for Nb-coated copper cavities. To overcome this challenge, we employed DC bias high-power impulse magnetron sputtering to deposit …

Detecting Sars-Cov-2 In Ct Scans Using Vision Transformer And Graph Neural Network, Kamorudeen Amuda, Almustapha Wakili, Tomilade Amoo, Lukman Agbetu, Qianlong Wang, Jinjuan Feng

Electrical & Computer Engineering Faculty Publications

The COVID-19 pandemic has presented significant challenges to global healthcare, bringing out the urgent need for reliable diagnostic tools. Computed Tomography (CT) scans have proven instrumental in detecting COVID-19-induced lung abnormalities. This study introduces Convolutional Neural Network, Graph Neural Network, and Vision Transformer (ViTGNN), an advanced hybrid model designed to enhance SARS-CoV-2 detection by combining Graph Neural Networks (GNNs) for feature extraction with Vision Transformers (ViTs) for classification. Using the strength of CNN and GNN to capture complex relational structures and the ViT capacity to classify global contexts, ViTGNN achieves a comprehensive representation of CT scan data. The model was …

High-Fidelity Soh Prediction In Lithium-Ion Batteries Using Hybrid Ml Networks, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Accurate and efficient prediction of lithium-ion battery state of health (SOH) is critical for ensuring reliability in electric vehicles, grid storage, and aerospace systems. Traditional SOH estimation methods often struggle with nonlinear degradation behaviors and lack sensitivity to subtle electrochemical signals, limiting their real-world deployment. To address these challenges, this study examines hybrid deep learning models that integrate differential capacity (dQ/dV) analysis to enhance predictive accuracy. Four hybrid architectures - hybrid CNN-LSTM multihead, CNN extractor for LSTM, DNN-LSTM, and DNN Bi-LSTM - were developed and evaluated using the NASA randomized battery usage dataset, offering a realistic benchmark under diverse operational …

Time-Marching Quantum Algorithm For Simulation Of Nonlinear Lorenz Dynamics, Efstratios Koukoutsis, George Vahala, Min Soe, Kyriakos Hizanidis, Linda Vahala, Abhay K. Ram

Electrical & Computer Engineering Faculty Publications

Simulating nonlinear classical dynamics on a quantum computer is an inherently challenging task due to the linear operator formulation of quantum mechanics. In this work, we provide a systematic approach to alleviate this difficulty by developing an explicit quantum algorithm that implements the time evolution of a second-order time-discretized version of the Lorenz model. The Lorenz model is a celebrated system of nonlinear ordinary differential equations that has been extensively studied in the contexts of climate science, fluid dynamics, and chaos theory. Our algorithm possesses a recursive structure and requires only a linear number of copies of the initial state …

Energy-Aware Swarm Robotics In Smart Microgrids Using Quantum-Inspired Reinforcement Learning, Mohamed Shili, Salah Hammedi, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

The integration of autonomous robots with intelligent electrical systems introduces complex energy management challenges, particularly as microgrids increasingly incorporate renewable energy sources and storage devices in widely distributed environments. This study proposes a quantum-inspired multi-agent reinforcement learning (QI-MARL) framework for energy-aware swarm coordination in smart microgrids. Each robot functions as an intelligent agent capable of performing multiple tasks within dynamic domestic and industrial environments while optimizing energy utilization. The quantum-inspired mechanism enhances adaptability by enabling probabilistic decision-making, allowing both robots and microgrid nodes to self-organize based on task demands, battery states, and real-time energy availability. Comparative experiments across 1500 grid-based …

The Effect Of Electrode Geometry On Excited Species Production In Atmospheric Pressure Air-Hydrogen Streamer Discharge, Shirshak Kumar Dhali, Stuart Reyes

Electrical & Computer Engineering Faculty Publications

When a gas is overvolted at or near atmospheric pressure, it results in a streamer discharge formation. Electrode geometries exert significant impact on the electrical breakdown of gases by altering the spatial profile of the electric field. In many applications the efficient generation of radicals is critical and is determined by the characteristics of the streamer discharge. We examine the effect of electrode geometry on the streamer characteristics and the production of radicals. This is performed for three different electrode geometries: plane–plane, pin–plane, and pin–pin. A two-dimensional rotationally symmetric fluid model is used for the streamer discharge simulation in the …

The Effect Of Electrode Geometry On Excited Species Production In Atmospheric Pressure Air–Hydrogen Streamer Discharge, Shirshak Kumar Dhali, Stuart Reyes

Electrical & Computer Engineering Faculty Publications

When a gas is overvolted at or near atmospheric pressure, it results in a streamer discharge formation. Electrode geometries exert significant impact on the electrical breakdown of gases by altering the spatial profile of the electric field. In many applications the efficient generation of radicals is critical and is determined by the characteristics of the streamer discharge. We examine the effect of electrode geometry on the streamer characteristics and the production of radicals. This is performed for three different electrode geometries: plane–plane, pin–plane, and pin–pin. A two-dimensional rotationally symmetric fluid model is used for the streamer discharge simulation in the …

Input Independent Observers For Bilinear Systems Using Convex Optimization, M. Aminul Haq, W. Steven Gray

Electrical & Computer Engineering Faculty Publications

An asymptotic state variable observer is proposed for a continuous-time bilinear dynamical system with the distinguishing feature that the error dynamics are globally asymptotically stable and independent of the applied input. Only the speed of convergence of the error dynamics may be input dependent. The approach is to apply classical Lyapunov stability theory using a convex optimization algorithm and linear matrix inequality (LMI) tools to in effect isolate the stability property of the error dynamics from the input. The LMIs are used to turn the nonconvex problem into a convex problem. The method is demonstrated on an induction motor drive.

Are We Ready For Synchronous Conceptual Modeling In Augmented Reality? A Usability Study On Causal Maps With Hololens 2, Anish Shrestha, Philippe J. Giabbanelli

VMASC Publications

(1) Background: Participatory modeling requires combining individual views to create a shared conceptual model. While remote collaboration tools have enabled synchronous online modeling, they are limited to desktop settings. Augmented reality (AR) offers a new approach by potentially providing the sense of presence found in physical collaboration, which may better support participants in achieving the sense of presence found in physical locations, thus supporting them in negotiating meaning and building a shared model. (2) Methods: Building on prior works that developed technology, we performed a usability study with pairs of modelers to examine their ability at performing key conceptual modeling …

The Rise And Fall Of Religion: An Agent-Based Model Of Secularisation, Security And Prosociality, Ivan Puga-Gonzalez, F. Leron Shults, Ross Gore, Konrad Talmont-Kaminski

Center for Secure and Intelligent Critical Systems (CSICS) Publications

The relationship between religion, society, and individual behaviour has been a subject of extensive inquiry, drawing upon a rich collection of historical and contemporary perspectives. The scientific study of religion at the social level has often found its roots in the foundational work of Durkheim (Durkheim, 1912), who posited that religion serves as a catalyst for social order and the promotion of prosocial behaviour. At the same time, Malinowski’s observations regarding the connection between ritual and anxiety have led to a number of lines of inquiry that have come to extend to other aspects of religion. Yet, taken together, these …