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Volume 34, Number 2, Summer/Fall 2025, Office Of Communications, Illinois Wesleyan University

Illinois Wesleyan University Magazine, 2018-present

VOLUME 34 | NUMBER 2 | Summer/Fall 2025

ON OUR COVER:

The Illinois Wesleyan University archives, housed on the fourth floor of The Ames Library, holds many artifacts of IWU history, including the original university charter and a gold medal awarded to John Marden, clas of 1909, for his breakthrough work in atomic science and engineering.

18 175 Years of Illinois Wesleyan University. Celebrate IWU's history with a timeline of the last 175 years of our community's milestones.

26 Alumni Award Winners. Meet our Award Winners John Camardella '03, Natalie Lalagos '12, and Carol Willis '68.

The Mental Health Bill (2025) For England And Wales: Professional And Carer Consensus Statement Summarising Concerns And Unintended Consequences From Proposed Changes To Autism And Learning Disability, Rohit Shankar, Peter Beazley

Peninsula Medical School

The Mental Health Bill, 2025, proposes to remove autism and learning disability from the scope of Section 3 of the Mental Health Act, 1983 (MHA). The present article represents a professional and carer consensus statement that raises concerns and identifies probable unintended consequences if this proposal becomes law. Our concerns relate to the lack of clear mandate for such proposals, conceptual inconsistency when considering other conditions that might give rise to a need for detention and the inconsistency in applying such changes to Part II of the MHA but not Part III. If the proposed changes become law, we anticipate …

The B2biers System: A Content-Based Perspective On Maximizing Influence And Subscription In Social Networks, Konstantinos Theocharidis, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

The popular problem of Influence Maximization (IM) asks for the k users who can maximize the influence of a fixed post in a social network. In contrast, the problem of Content- Aware Influence Maximization (CAIM) asks for the k features to form a viral tunable post in a social network starting its diffusion from a fixed set of initial adopters. CAIM paves the way for a number of novel problems to be studied that altogether can lead to the development of a system that would be valuable for advertisers who manage social network pages. This holds since features (brands) in …

Position: Trustworthy Ai Agents Require The Integration Of Large Language Models And Formal Methods, Yedi Zhang, Yufan Cai, Xinyue Zuo, Xiaokun Luan, Kailong Wang, Zhe Hou, Yifan Zhang, Zhiyuan Wei, Meng Sun, Jun Sun, Jing Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing broad aspects of daily life. Despite their remarkable performance, LLMs exhibit a fundamental limitation: hallucination—the tendency to produce misleading outputs that appear plausible. This inherent unreliability poses significant risks, particularly in high-stakes domains where trustworthiness is essential. On the other hand, Formal Methods (FMs), which share foundations with symbolic AI, provide mathematically rigorous techniques for modeling, specifying, reasoning, and verifying the correctness of systems. These methods have been widely employed in mission-critical domains such as aerospace, defense, and cybersecurity. However, the broader adoption of FMs remains constrained …

Unified Neural Backdoor Removal With Only Few Clean Samples Through Unlearning And Relearning, Nay Myat Min, Long H. Pham, Jun Sun

Research Collection School Of Computing and Information Systems

Deep neural networks have achieved remarkable success across various applications; however, their vulnerability to backdoor attacks poses severe security risks—especially in situations where only a limited set of clean samples is available for defense. In this work, we address this critical challenge by proposing ULRL (UnLearn and ReLearn for backdoor removal), a novel two-phase approach for comprehensive backdoor removal. Our method first employs an unlearning phase, in which the network’s loss is intentionally maximized on a small clean dataset to expose neurons that are excessively sensitive to backdoor triggers. Subsequently, in the relearning phase, these suspicious neurons are recalibrated using …

Advancing Food Nutrition Estimation Via Visual-Ingredient Feature Fusion, Huiyan Qi, Bin Zhu, Chong-Wah Ngo, Jingjing Chen, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Nutrition estimation is an important component of promoting healthy eating and mitigating diet-related health risks. Despite advances in tasks such as food classification and ingredient recognition, progress in nutrition estimation is limited due to the lack of datasets with nutritional annotations. To address this issue, we introduce FastFood, a dataset with 84,446 images across 908 fast food categories, featuring ingredient and nutritional annotations. In addition, we propose a new model-agnostic Visual-Ingredient Feature Fusion (VIF2 ) method to enhance nutrition estimation by integrating visual and ingredient features. Ingredient robustness is improved through synonym replacement and resampling strategies during training. The ingredient-aware …

Unbounded Multi-Hop Proxy Re-Encryption With Hra Security: An Lwe-Based Optimization, Xiaohan Wan, Yang Wang, Haiyang Xue, Mingqiang Wang

Research Collection School Of Computing and Information Systems

Proxy re-encryption (PRE) schemes enable a semi-honest proxy to transform a ciphertext of one user i to another user j while preserving the privacy of the underlying message. Multi-hop PRE schemes allow a legal ciphertext to undergo multiple transformations, but for lattice-based multi-hop PREs, the number of transformations is typically bounded due to the increase of error terms. Recently, Zhao et al. (ESORICS 2024) introduced a lattice-based unbounded multi-hop (homomorphic) PRE scheme that supports an unbounded number of hops. Nevertheless, their scheme only achieves the selective CPA security. In contrast, Fuchsbauer et al. (PKC 2019) proposed a generic framework for …

An Incentive Mechanism For Privacy Preserved Data Trading With Verifiable Data Disturbance, Man Zhang, Xinghua Li, Bin Luo, Yanbing Ren, Yinbin Miao, Ximeng Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

To motivate data owners’ (DOs’) trading willingness, the existing incentive mechanisms allow DOs to independently disturb data following data consumer's (DC’s) availability requirement. However, they cannot motivate DOs’ honest disturbance, which is attributed to DOs’ independent disturbance without any supervision. Thus, we implement an incentive mechanism for privacy preserved data trading with verifiable data disturbance where an honest-but-curious disturbance generator (DG) is additionally introduced to supervise DOs’ local disturbance and assist disturbance verification between DOs and DC. Specifically, DG generates the disturbance strategies and secretly distributes to DOs following private information retrieval, guaranteeing DOs's local disturbance's privacy and verifiability with …

Action Dubber: Timing Audible Actions Via Inflectional Flow, Wenlong Wan, Weiying Zheng, Tianyi Xiang, Guiqing Li, Shengfeng He

Research Collection School Of Computing and Information Systems

We introduce the task of Audible Action Temporal Localization, which aims to identify the spatiotemporal coordinates of audible movements. Unlike conventional tasks such as action recognition and temporal action localization, which broadly analyze video content, our task focuses on the distinct kinematic dynamics of audible actions. It is based on the premise that key actions are driven by inflectional movements; for example, collisions that produce sound often involve abrupt changes in motion. To capture this, we propose T A2Net, a novel architecture that estimates inflectional flow using the second derivative of motion to determine collision timings without relying on audio …

Leakage-Resilient Easily Deployable And Efficiently Searchable Encryption (Edese), Jiaming Yuan, Yingjiu Li, Jun Li, Daoyuan Wu, Jianting Ning, Yangguang Tian, Robert H. Deng

Research Collection School Of Computing and Information Systems

Easily Deployable and Efficiently Searchable Encryption (EDESE) is a cryptographic primitive designed for practical searchable applications, offering efficient search and easy deployment. However, it remains vulnerable to Leakage-Abuse attacks, allowing adversaries to exploit keyword-matching processes to extract sensitive information. To address these vulnerabilities, we introduce Leakage-Resilient EDESE (LR-EDESE) with k-indistinguishability and controlled leakage functions. We then propose Volume Leakage-Resilient EDESE (VLR-EDESE), a new scheme to protect against both query and document volume leakage. Our experimental results demonstrate that at k = 5000 (maximum security setting), VLR-EDESE incurs an overhead of 63× compared to the baseline EDESE without leakage protection, outperforming …

Llm-Based Multi-Agent Systems For Software Engineering: Literature Review, Vision And The Road Ahead, Junda He, Christoph Treude, David Lo

Research Collection School Of Computing and Information Systems

Integrating Large Language Models (LLMs) into autonomous agents marks a significant shift in the research landscape by offering cognitive abilities that are competitive with human planning and reasoning. This paper explores the transformative potential of integrating Large Language Models into Multi-Agent (LMA) systems for addressing complex challenges in software engineering (SE). By leveraging the collaborative and specialized abilities of multiple agents, LMA systems enable autonomous problem-solving, improve robustness, and provide scalable solutions for managing the complexity of real-world software projects. In this paper, we conduct a systematic review of recent primary studies to map the current landscape of LMA applications …

Surrogate Learning In Meta-Black-Box Optimization: A Preliminary Study, Zeyuan Ma, Zhiyang Huang, Jiacheng Chen, Zhiguang Cao, Yue-Jiao Gong

Research Collection School Of Computing and Information Systems

Recent Meta-Black-Box Optimization (MetaBBO) approaches have shown possibility of enhancing the optimization performance through learning meta-level policies to dynamically configure low-level optimizers. However, existing MetaBBO approaches potentially consume massive function evaluations to train their meta-level policies. Inspired by the recent trend of using surrogate models for cost-friendly evaluation of expensive optimization problems, in this paper, we propose a novel MetaBBO framework which combines surrogate learning process and reinforcement learning-aided Differential Evolution algorithm, namely Surr-RLDE, to address the intensive function evaluation in MetaBBO. Surr-RLDE comprises two learning stages: surrogate learning and policy learning. In surrogate learning, we train a Kolmogorov-Arnold Networks …

Collaboration With Dynamic Open Ad Hoc Team Via Team State Modelling, Jing Sun, Cong Zhang, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Open ad hoc teamwork presents the challenging problem of designing an autonomous agent that can rapidly adapt to collaborate with teammates without prior coordination in an open environment. Existing methods primarily rely on fixed, predefined teammate types, overlooking the fact that teammates may change dynamically. To address this limitation, we propose a novel reinforcement learning approach, the Open Online Teammate Adaptation Framework (Open-OTAF), which enables a controlled agent to collaborate with dynamic teammates in open ad hoc environments. To achieve this, the controlled agent employs a dual teamwork situation inference model to capture the current teamwork state, facilitating decision-making under …

A Mixed-Curvature Based Pre-Training Paradigm For Multi-Task Vehicle Routing Solver, Suyu Liu, Zhiguang Cao, Shanshan Feng, Yew-Soon Ong

Research Collection School Of Computing and Information Systems

Solving various types of vehicle routing problems (VRPs) using a unified neural solver has garnered significant attentions in recent years. Despite their effectiveness, existing neural multi-task solvers often fail to account for the geometric structures inherent in different tasks, which may result in suboptimal performance. To address this limitation, we propose a curvature-aware pre-training framework. Specifically, we leverage mixed-curvature spaces during the feature fusion stage, encouraging the model to capture the underlying geometric properties of each instance. Through extensive experiments, we evaluate the proposed pre-training strategy on existing neural multi-task solvers across a variety of testing scenarios. The results demonstrate …

Shield: Multi-Task Multi-Distribution Vehicle Routing Solver With Sparsity And Hierarchy, Yong Liang Goh, Zhiguang Cao, Yining Ma, Jianan Zhou, Mohammed Haroon Dupty, Wee Sun Lee

Research Collection School Of Computing and Information Systems

Recent advances toward foundation models for routing problems have shown great potential of a unified deep model for various VRP variants. However, they overlook the complex real-world customer distributions. In this work, we advance the Multi-Task VRP (MTVRP) setting to the more realistic yet challenging Multi-Task Multi-Distribution VRP (MTMDVRP) setting, and introduce SHIELD, a novel model that leverages both sparsity and hierarchy principles. Building on a deeper decoder architecture, we first incorporate the Mixture-of-Depths (MoD) technique to enforce sparsity. This improves both efficiency and generalization by allowing the model to dynamically select nodes to use or skip each decoder layer, …

Ts-Diff: Two-Stage Diffusion Model For Low-Light Raw Image Enhancement, Yi Li, Zhiyuan Zhang, Jiangnan Xia, Jianghan Cheng, Qilong Wu, Junwei Li

Research Collection School Of Computing and Information Systems

This paper presents a novel Two-Stage Diffusion Model (TS-Diff) for enhancing extremely low-light RAW images. In the pre-training stage, TS-Diff synthesizes noisy images by constructing multiple virtual cameras based on a noise space. Camera Feature Integration (CFI) modules are then designed to enable the model to learn generalizable features across diverse virtual cameras. During the aligning stage, CFIs are averaged to create a target-specific CFIT, which is fine-tuned using a small amount of real RAW data to adapt to the noise characteristics of specific cameras. A structural reparameterization technique further simplifies CFIT for efficient deployment. To address color shifts during …

Sparse-To-Dense: A Free Lunch For Lossless Acceleration Of Video Understanding In Llms, Xuan Zhang, Cunxiao Du, Sicheng Yu, Jiawei Wu, Fengzhuo Zhang, Wei Gao, Qian Liu

Research Collection School Of Computing and Information Systems

Due to the auto-regressive nature of current video large language models (Video-LLMs), the inference latency increases as the input sequence length grows, posing challenges for the efficient processing of video sequences that are usually very long. We observe that during decoding, the attention scores of most tokens in Video-LLMs tend to be sparse and concentrated, with only certain tokens requiring comprehensive full attention. Based on this insight, we introduce Sparse-to-Dense (StD), a novel decoding strategy that integrates two distinct modules: one leveraging sparse top-K attention and the other employing dense full attention. These modules collaborate to accelerate Video-LLMs without loss. …

Rustmap: Towards Project-Scale C-To-Rust Migration Via Program Analysis And Llm, Xuemeng Cai, Jiakun Liu, Xiping Huang, Yijun Yu, Haitao Wu, Chunmiao Li, Bo Wang, Imam Nur Bani Yusuf, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Migrating existing C programs into Rust is increasingly desired, as Rust offers superior memory safety while maintaining C’s high performance. Existing automated translation tools, such as C2Rust, may rely too much on syntactic, template-based translation and generate unsafe Rust code that is hard for human developers to read, maintain, or even compile. More semantic-aware translation that produces safer, idiomatic, and runnable Rust code is much needed. This paper introduces a novel dependency-guided and large language model (LLM)-based C-to-Rust translation approach, RustMap, based on three key ideas: (1) Utilize LLM’s capabilities to produce idiomatic Rust code from given small pieces of …

Quantum Technologies In Decentralisation, Paul Robert Griffin, Rudy Raymond, Tsuyoshi Idé

Research Collection School Of Computing and Information Systems

Quantum technologies, rooted in the manipulation of quantum information, are revolutionizing computing and networking domains. Their impact on blockchains and decentralized systems is twofold. While much attention has been given to the potential of quantum computing to attack blockchains, these advanced technologies also offer avenues for strengthening and optimizing them. This chapter delves into the intricacies of quantum technologies, from the foundational concepts of qubits, quantum gates, and quantum networks to their implications for blockchains. We explore both the vulnerabilities of blockchains in a quantum-dominant era and the promising solutions quantum technologies provide, culminating in a use case examining their …

Recruitment And Retention Of Intensive Care Unit Survivors In Follow-Up Studies: A Systematic Review, Beverley Ewens, Vivien Kemp, Yvonne Middlewick, Amanda Towell-Barnard, Lisa Whitehead

Research outputs 2022 to 2026

Background: Engaging intensive care unit survivors in research is challenging. Studies have reported recruitment and attrition rates; details are lacking on retention strategies and attrition. Objective: The aim of this study was to explore barriers and enablers to recruitment and retention in research of people post intensive care discharge. Methods: A convergent mixed-method review using the Joanna Briggs Institute (JBI) methodology considered studies that reported on recruitment, retention, and attrition rates of adult post–intensive care survivors in longitudinal studies. CINAHL Ultimate (CINAHL+), PubMed, Excerpta Medica Database (EMBASE), PsycINFO, Scopus, Proquest Health, and Medical Collection were searched in March 2024 using …

The Employment Situation Of Veterans: July 2025, Institute For Veterans And Military Families At Syracuse University

Institute for Veterans and Military Families

In July 2025, veteran unemployment dropped significantly to 3.0 percent, down from 3.7 percent in June, reflecting stronger labor outcomes compared to nonveterans. Post‑9/11 veteran unemployment also declined to 3.1 percent. Younger veterans experienced major improvements, with unemployment among those aged 18–24 falling from 6.2 percent to 1.8 percent. Most veteran age groups saw declines, except ages 35–44 and 55–64, which saw slight increases. Male veteran unemployment decreased to 2.7 percent, while female veteran unemployment held steady at 4.4 percent. Overall, veterans continued to maintain lower unemployment rates than nonveterans.

Investigating The Thixotropy Of Fresh Struvite Cement-Based Composite: Insights On Mechanisms Of The Pastes’ Thixotropic Behavior, Ugochukwu Ewuzie, Abdulkareem O. Yusuf, Damilola Daramola, Monday Uchenna Okoronkwo

Chemical and Biochemical Engineering Faculty Research & Creative Works

Struvite (ST) recovered during wastewater treatment has been sparsely applied in cement-based composites. This study systematically evaluated the thixotropic behavior of cement-struvite (CST) pastes, a mix of 5–20 % ST by mass of cement, and proposed the interaction mechanisms leading to the pastes' thixotropy. The hysteresis loop area was used to establish the pastes' thixotropy and investigate its relationship with increased ST content, temperature, and yield stress. In the thixotropic behavior model used, the equilibrium shear stress was employed to examine the CST pastes' irreversible change; the characteristic time of deflocculation was used to study the flocs destruction process; and …

Gallium-Containing Bioactive Glasses: Their Influence On Ion Release And The Bioactivity Of Resulting Glass Polyalkenoate Cements, Lana Margaret Placek, Danielle Lee Perry, Mark Robert Towler, Anthony William Wren

Chemical and Biochemical Engineering Faculty Research & Creative Works

A series of glasses (0.48SiO2 − [0.40-x]ZnO − 0.12CaO-xGa2O3, x = 0, 0.8, 0.16) was developed to formulate a series of Ga-containing glass polyalkenoate cements (GPCs). The solubility of GPCs was tested using DI water, and it was found that the sample containing the highest mol% of Ga, LGa-2, had the most Ga ion release. The GPCs were incubated in SBF, and SEM/EDS analysis revealed that the at% of P increased, while the at% of Si decreased, highlighting the CaP precipitation on the GPC surface. The at% of Ga also decreased, reinforcing the Ga release from the GPC. Cellular testing …

Retraction: A Database Of Teleseismic Shear-Wave Splitting Measurements For The Ordos Block And Adjacent Areas(Seismological Research Letters (2022), 93, 5, (2731–2739), 10.1785/0220210310), Lin Liu, Stephen S. Gao, Kelly H. Liu, Tu Xue, Yan Jia, Sanzhong Li

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

An earlier version of this article (Liu et al., 2022) included private data from the Himalayan-III program which should not have been made public. The authors acknowledge and regret their negligence during the selection of the measurements. The impacted data represent only 2.7% of the total data published in this article, and after review, the authors and the editors agree that this unintentional error has no bearing on the work's scientific conclusions. Therefore, we are retracting the impacted data and have made corrections to remove any Himalayan-III program data from the article's text, figures, and supplemental tables.

Public Spaces For Community Campuses And Universities, Marichela Sepe

Books and Monographs

Chapter: Modern Pedestrian Campus Design in North America, 1940s-70s, Eric Mumford, pages 13-22

This volume explores the growing significance of open public spaces within università campuses—spaces that go far beyond their functional role to become essential arenas for social interaction, informal learning, well-being, and urban integration.

Structured around three interconnected themes—Campus and Public Spaces, Campus and University Communities, and Campus and the City—the volume gathers international best practices, offering an insightful tool for students, academics, designers, administrators, and urban thinkers.

Full text also available for download at https://www.inuedizioni.com/en/prodotti/pubblicazione/public-spaces-community-campuses-and-universities

Civilian Enforcers, Karen Pita Loor

Faculty Scholarship

This Article analyzes the largely unexplored phenomenon of militant civilians engaged in efforts to police and silence activism that challenges entrenched American power systems and economic distributions placing whites atop the social hierarchy in the United States. I argue that this civilian enforcement is an unregulated vessel for state-sponsored violence meant to silence the contestation of the existing racial hierarchy. While scholars, myself included, have written about the many ways police confront and silence racial justice activists on the streets at least since the beginning of the Black Lives Matter (BLM) movement, the role law enforcement plays in silencing racial …

"What Shall Be Orthodox" In Polarized Times: Overview And Response To Commentators, Linda C. Mcclain, James E. Fleming

Faculty Scholarship

“If there is any fixed star in our constitutional constellation, it is that no official, high or petty, can prescribe what shall be orthodox in politics, nationalism, religion, or other matters of opinion or force citizens to confess by word or act their faith therein.” Justice Robert Jackson wrote this celebrated passage in his majority opinion in West Virginia State Board of Education v. Barnette (1943), which protected the First Amendment right of Jehovah’s Witness children not to participate in a compulsory flag salute in public schools. In recent years, protests against imposed orthodoxy—usually invoking Barnette—have occurred in …

A Historical Case For A Robust But Non-Remedial Seventh Amendment, Jed Handelsman Shugerman

Faculty Scholarship

In Jarkesy, the Supreme Court rightly held that the Seventh Amendment required a jury trial for a case fundamentally similar to common law fraud, and it rightly limited the scope of the “public rights” exception to the Seventh Amendment. Grounded in historical and originalist methods, this essay makes four suggestions after Jarkesy:

1. Following Jarkesy, the judiciary should continue a more robust enforcement of the Seventh Amendment right to a jury trial. The courts should eliminate the “public rights” exception to the Seventh Amendment, which does not appear to have an original link to the Seventh Amendment. The …

Feasibility Of Applying Bacillus Amyloliquefaciens-Derived Solid State Fermentation Products Into The Hatch Cabinet Environment As A Method To Mitigate The Microbial Bloom During The Hatching Phase Authors, Mitchell C. Rowland, Lucas E. Graham, Callie Selby, Aaron J. Forga, Billy M. Hargis, Christine N. Voung, Graham Danielle

Poultry Science Faculty Publications and Presentations

Formaldehyde has been used to control microbial contamination in commercial hatch cabinets. The purpose of the present study was to investigate the effects of spray application of Bacillus amyloliquefaciens solid state fermentation products on the microbial load in the hatch cabinet, pioneer colonization of the gastrointestinal tract (GIT), and early performance compared to formaldehyde fumigation. An environmental challenge model was used to simulate the microbial bloom to compare the application of two B. amyloliquefaciens strains (MCR002, MCR009) to formaldehyde fumigation. Groups included 1) non-challenged control (NC), 2) challenged with pathogen mix (PM) containing Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus …

Evaluation Of The Incremental Effect Of Fasting Length On Ph, Select Cecal Microbial Groups, Cecal Volatile Fatty Acid Concentrations, And Secretory Iga Excretion In Roosters, B.W. Parsons, M.R. Bedford, C.L. Wyatt

Poultry Science Faculty Publications and Presentations

Two experiments were conducted to evaluate the effect of incremental fasting time on the gastrointestinal tract in chickens. Adult White Leghorn roosters with intact ceca were provided a nutrient-adequate corn-soybean meal diet ad libitum for 3 weeks. Prior to initiation of the experimental phase, ad libitum feed intake was recorded for 8 h and immediately after the fasting period commenced. In Experiment 1, roosters were fasted for either 0, 3, 6, 9, 12, 16, or 24 h. At each time point birds were euthanized and pH in the crop, gizzard, and ceca were recorded and cecal contents were collected to …