Physical Sciences and Mathematics Commons^™

Against The Substitutive Approach To Ai In Healthcare, Rand Hirmiz

Research Collection School of Social Sciences

Paul Bloom has famously argued against the need for empathy in clinicians, while Sally Dalton-Brown has argued that AI need not be capable of empathy to be a good carer. In this paper, the capacity for AI to substitute for human clinicians is assessed from a bioethical perspective, primarily through the evaluation of the arguments put forth by Dalton-Brown and Bloom concerning empathy in healthcare. In opposition to both Bloom and Dalton-Brown, this paper argues that (1) empathy is essential to providing good care or deep care (that is, care that goes beyond the mere fulfilment of medical tasks), (2) …

The Epistemic Role Of Ai Decision Support Systems: Neither Superiors, Nor Inferiors, Nor Peers, Rand Hirmiz

Research Collection School of Social Sciences

Despite the importance of discussions over the epistemic role that artificially intelligent decision support systems ought to play, there is currently a lack of these discussions in both the AI literature and the epistemology literature. My goal in this paper is to rectify this by proposing an account of the epistemic role of AI decision support systems in medicine and discussing what this epistemic role means with regard to how these systems ought to be utilized. In particular, I argue that AI decision support systems are not epistemic superiors, inferiors, or peers. Instead, I recommend that they be classified in …

The Novel Estrogen Receptor Beta Agonist Egx358 And Apoe Genotype Influence Memory, Vasomotor, And Anxiety Outcomes In An Alzheimer’S Mouse Model, M. R. Schwabe, A. W. Fleischer, R. K. Kuehn, S. Chaudhury, J. M. York, D. S. Sem, William A. Donaldson, M. J. Ladu, K. M. Frick

Chemistry Faculty Research and Publications

Introduction: Alzheimer’s disease (AD) prevalence and severity are associated with increased age, female sex, and apolipoprotein E4 (APOE4) genotype. Although estrogen therapy (ET) effectively reduces symptoms of menopause including hot flashes and anxiety, and can reduce dementia risk, it is associated with increased risks of breast and uterine cancer due to estrogen receptor alpha (ERα)-mediated increases in cancer cell proliferation. Because ERβ activation reduces this cell proliferation, selective targeting of ERβ may provide a safer method of improving memory and reducing hot flashes in menopausal women, including those with AD. APOE genotype influences the response to ET, although it is …

Liquid Crystalline Collagen Assemblies As Substrates For Directed Alignment Of Human Schwann Cells, Homa Ghaiedi, Luis Carlos Pinzon-Herrera, Saja Alshafeay, Leonard Harris, Jorge Almodovar, Karthik Nayani

Chemical Engineering Faculty Publications and Presentations

Collagen is a key component of the extracellular matrix (ECM) and well-oriented domains of collagen are important for mimicking the local cell environment in vitro. While there has been significant attention directed towards the alignment of collagen, formation of large-scale oriented domains remains a key challenge. Type I collagen self-assembles to form liquid crystalline (LC) mesophases in acidic conditions at concentrations above 100 mg mL−1. The LC mesophase provides an efficient platform for large-scale alignment and patterning of collagen coated substrates. However, there still exist challenges related to solubilizing and processing of collagen at such high concentrations in order …

An Efficient Pairing-Free Ciphertext-Policy Attribute-Based Encryption Scheme For Internet Of Things, Chong Guo, Bei Gong, Muhammad Waqas, Hisham Alasmary, Shanshan Tu, Sheng Chen

Research outputs 2022 to 2026

The Internet of Things (IoT) is a heterogeneous network composed of numerous dynamically connected devices. While it brings convenience, the IoT also faces serious challenges in data security. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography method that supports fine-grained access control, offering a solution to the IoT’s security issues. However, existing CP-ABE schemes are inefficient and unsuitable for IoT devices with limited computing resources. To address this problem, this paper proposes an efficient pairing-free CP-ABE scheme for the IoT. The scheme is based on lightweight elliptic curve scalar multiplication and supports multi-authority and verifiable outsourced decryption. The proposed scheme …

Mid-Infrared Spectroscopy Determines The Provenance Of Coastal Marine Soils And Their Organic And Inorganic Carbon Content, Lewis Walden, Oscar Serrano, Zefang Shen, Mingxi Zhang, Paul Lavery, Zhongkui Luo, Lei Gao, Raphael A. Viscarra Rossel

Research outputs 2022 to 2026

Vegetated coastal ecosystems (VCE), encompassing tidal marshes, mangroves, and seagrasses, serve as significant ‘blue’ carbon (C) sinks. Improving our understanding of VCE soils and their spatial and temporal dynamics is essential for conservation efforts. Conventional methods to characterise the dynamics and provenance of VCE soils and measure their total organic carbon (TOC) and inorganic carbon (TIC) contents are cumbersome and expensive. We recorded the mid-infrared (MIR) spectra and measured the TOC and TIC content of 323 subsamples across consistent depths from 106 soil core samples. Using the spectra of each VCE, we determined their mineral and organic composition by depth. …

Chronological Progress In Enhancing Cigs Solar Cell Performance Through Window Layer Development: Fundamentals, Synthesis, Optimization, Nadia Hartini Suhaimi, Mohammad Nur-E-Alam, Boon Kar Yap, K. Sobayel, Md Helal Miah, Islam, Sieh Kiong Tiong, Narottam Das, Mayeen Uddin Khandakher, Nowshad Amin

Research outputs 2022 to 2026

Several factors, particularly the material of the window layer, contribute to the efficiency of CIGS solar cells. To optimize light absorption and reduce energy losses, it is critical to select the appropriate material for the window layer development. Thus, the main emphasis of this review is on the development of window layers, covering fundamental concepts, synthesis techniques, characterization methods, and optimization strategies. Metal oxides and doped metal oxides are critical materials for optimizing charge carrier flow, minimizing energy loss, and elevating sunlight transmission to the CIGS absorber. Despite tremendous progress, difficulties such as increased conductivity, transparency, stability, and cost-effectiveness remain. …

Microplastic Pollution In Riparian Soils Of The Rapidly Growing City Of Thimphu, Bhutan, Karma Jamtsho, Mark A. Lund, David Blake, Eddie Van Etten

Research outputs 2022 to 2026

Plastic has become a vitally important material for humans; however, the large amount of plastic waste generated annually pollutes the environment. Plastic decomposition generates microplastics (MPs), which have emerged as a concerning global environmental pollutant because of their potential to be more harmful to the environment than their larger counterparts. This study examined the occurrence and abundance of MPs in riparian soils (RS) of a rapidly growing city in Thimphu, Bhutan. Additionally, the study investigated the relationships between the abundance of MP and several variables, such as the physicochemical properties of the soil, land use, the distance to impervious cover …

Exploring The Human Side Of Math, Mike Janssen

Faculty Work Comprehensive List

"Abstract mathematics is an important way to better understand and marvel at the beauty and intricacy of God’s creation."

Posting about ­­­­­­­­experiences in math research from In All Things, an online hub that offers insight into maintaining and faithful and orthodox Reformed Christian worldview while fearlessly engaging in every aspect of contemporary life – until all is made new.

Exploring the Human Side of Math

Large-Scale Cosmic-Ray Anisotropies With 19yr Of Data From The Pierre Auger Observatory, A. Abdul Halim, P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, A. Almela, B. Fick, K. Nguyen, D. Nitz, Et Al.

Michigan Tech Publications

Results are presented for the measurement of large-scale anisotropies in the arrival directions of ultra–high-energy cosmic rays detected at the Pierre Auger Observatory during 19 yr of operation, prior to AugerPrime, the upgrade of the observatory. The 3D dipole amplitude and direction are reconstructed above 4 EeV in four energy bins. Besides the established dipolar anisotropy in R.A. above 8 EeV, the Fourier amplitude of the 8–16 EeV energy bin is now also above the 5σ discovery level. No time variation of the dipole moment above 8 EeV is found, setting an upper limit to the rate of change of …

Beyond Persuasion : Towards Conversational Recommender System With Credible Explanations, Peixin Qin, Chen Huang, Yang Deng, Wenqiang Lei, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

With the aid of large language models, current conversational recommender system (CRS) has gaining strong abilities to persuade users to accept recommended items. While these CRSs are highly persuasive, they can mislead users by incorporating incredible information in their explanations, ultimately damaging the long-term trust between users and the CRS. To address this, we propose a simple yet effective method, called PC-CRS, to enhance the credibility of CRS’s explanations during persuasion. It guides the explanation generation through our proposed credibility-aware persuasive strategies and then gradually refines explanations via post-hoc self-reflection. Experimental results demonstrate the efficacy of PC-CRS in promoting persuasive …

Balancing Visual Context Understanding In Dialogue For Image Retrieval, Zhaohui Wei, Lizi Liao, Xiaoyu Du, Xinguang Xiang

Research Collection School Of Computing and Information Systems

In the realm of dialogue-to-image retrieval, the primary challenge is to fetch images from a pre-compiled database that accurately reflect the intent embedded within the dialogue history. Existing methods often overemphasize inter-modal alignment, neglecting the nuanced nature of conversational context. Dialogue histories are frequently cluttered with redundant information and often lack direct image descriptions, leading to a substantial disconnect between conversational content and visual representation. This study introduces VCU, a novel framework designed to enhance the comprehension of dialogue history and improve cross-modal matching for image retrieval. VCU leverages large language models (LLMs) to perform a two-step extraction process. It …

Ultra-High Resolution Image Segmentation Via Locality-Aware Context Fusion And Alternating Local Enhancement, Wenxi Liu, Qi Li, Xindai Lin, Weixiang Yang, Shengfeng He, Yuanlong Yu

Research Collection School Of Computing and Information Systems

Ultra-high resolution image segmentation has raised increasing interests in recent years due to its realistic applications. In this paper, we innovate the widely used high-resolution image segmentation pipeline, in which an ultra-high resolution image is partitioned into regular patches for local segmentation and then the local results are merged into a high-resolution semantic mask. In particular, we introduce a novel locality-aware context fusion based segmentation model to process local patches, where the relevance between local patch and its various contexts are jointly and complementarily utilized to handle the semantic regions with large variations. Additionally, we present the alternating local enhancement …

Eyetraes : Fine-Grained, Low-Latency Eye Tracking Via Adaptive Event Slicing, Argha Sen, Panahetipola Mudiyanselage Nuwan Bandara, Ila Gokarn, Thivya Kandappu, Archan Misra

Research Collection School Of Computing and Information Systems

Eye-tracking technology has gained significant attention in recent years due to its wide range of applications in humancomputer interaction, virtual and augmented reality, and wearable health. Traditional RGB camera-based eye-tracking systems often struggle with poor temporal resolution and computational constraints, limiting their effectiveness in capturing rapid eye movements. To address these limitations, we propose EyeTrAES, a novel approach using neuromorphic event cameras for high-fidelity tracking of natural pupillary movement that shows significant kinematic variance. One of EyeTrAES’s highlights is the use of a novel adaptive windowing/slicing algorithm that ensures just the right amount of descriptive asynchronous event data accumulation within …

Efficient Multiplicative-To-Additive Function From Joye-Libert Cryptosystem And Its Application To Threshold Ecdsa, Haiyang Xue, Ho Man Au, Mengling Liu, Yin Kwan Chan, Handong Cui, Xiang Xie, Hon Tsz Yuen, Chengru Zhang

Research Collection School Of Computing and Information Systems

Threshold ECDSA receives interest lately due to its widespread adoption in blockchain applications. A common building block of all leading constructions involves a secure conversion of multiplicative shares into additive ones, which is called the multiplicative-to-additive (MtA) function. MtA dominates the overall complexity of all existing threshold ECDSA constructions. Specifically, O(n2) invocations of MtA are required in the case of n active signers. Hence, improvement of MtA leads directly to significant improvements for all state-of-the-art threshold ECDSA schemes.In this paper, we design a novel MtA by revisiting the Joye-Libert (JL) cryptosystem. Specifically, we revisit JL encryption and propose a JL-based …

Adversarial Learning For Coordinate Regression Through K-Layer Penetrating Representation, Mengxi Jiang, Yulei Sui, Yunqi Lei, Xiaofei Xie, Cuihua Li, Yang Liu, Ivor W. Tsang

Research Collection School Of Computing and Information Systems

Adversarial attack is a crucial step when evaluating the reliability and robustness of deep neural networks (DNNs) models. Most existing attack approaches apply an end-to-end gradient update strategy to generate adversarial examples for a classification or regression problem. However, few of them consider the non-differentiable DNN models (e.g., coordinate regression model) that prevent end-to-end backpropagation resulting in the failure of gradient calculation. In this paper, we present a new adversarial example generation approach for both untargeted and targeted attacks on coordinate regression models with non-differentiable operations. The novelty of our approach lies in a k-layer penetrating representation, on which we …

A Survey Of Ontology Expansion For Conversational Understanding, Jinggui Liang, Yuxia Wu, Yuan Fang, Hao Fei, Lizi Liao

Research Collection School Of Computing and Information Systems

In the rapidly evolving field of conversational AI, Ontology Expansion (OnExp) is crucial for enhancing the adaptability and robustness of conversational agents. Traditional models rely on static, predefined ontologies, limiting their ability to handle new and unforeseen user needs. This survey paper provides a comprehensive review of the state-of-the-art techniques in OnExp for conversational understanding. It categorizes the existing literature into three main areas: (1) New Intent Discovery, (2) New Slot-Value Discovery, and (3) Joint OnExp. By examining the methodologies, benchmarks, and challenges associated with these areas, we highlight several emerging frontiers in OnExp to improve agent performance in real-world …

Consecutive Batch Model Editing With Hook Layers, Shuaiyi Li, Yang Deng, Deng Cai, Hongyuan Lu, Liang Chen, Wai Lam

Research Collection School Of Computing and Information Systems

As the typical retraining paradigm is unacceptably time- and resource-consuming, researchers are turning to model editing to find an effective way that supports both consecutive and batch scenarios to edit the model behavior directly. Despite all these practical expectations, existing model editing methods fail to realize all of them. Furthermore, the memory demands for such sequential model editing approaches tend to be prohibitive, frequently necessitating an external memory that grows incrementally over time. To cope with these challenges, we propose CoachHooK, a model editing method that simultaneously supports sequential and batch editing. CoachHooK is memory-friendly as it only needs a …

Thoughts To Target: Enhance Planning For Target-Driven Conversation, Zhonghua Zheng, Lizi Liao, Yang Deng, Ee-Peng Lim, Minlie Huang, Liqiang Nie

Research Collection School Of Computing and Information Systems

In conversational AI, large-scale models excel in various tasks but struggle with target-driven conversation planning. Current methods, such as chain-of-thought reasoning and tree-search policy learning techniques, either neglect plan rationality or require extensive human simulation procedures. Addressing this, we propose a novel two-stage framework, named EnPL, to improve the LLMs’ capability in planning conversations towards designated targets, including (1) distilling natural language plans from target-driven conversation corpus and (2) generating new plans with demonstration-guided in-context learning. Specifically, we first propose a filter approach to distill a high-quality plan dataset, ConvPlan1. With the aid of corresponding conversational data and support from …

Bibliography For "3-D Printing Display", Isabella Piechota, Arianna Tillman, Annikah Carpio

Library Displays and Bibliographies

A bibliography created to support a display about 3D printing at the Leatherby Libraries during November 2024-February 2025 at the Leatherby Libraries at Chapman University.

Insulator-To-Metal Transition And Isotropic Gigantic Magnetoresistance In Layered Magnetic Semiconductors, Gokul Acharya, Bimal Neupane, Chia-Hsiu Hsu, Xian P. Yang, David Graf, Eun Sang Choi, Krishna Pandey, Md Rafique Un Nabi, Santosh Karki Chhetri, Rabindra Basnet, Sumaya Rahman, Jian Wang, Zhengxin Hu, Bo Da, Hugh O.H. Churchill, Guoqing Chang, M. Zahid Hasan, Yuanxi Wang, Jin Hu

Physics Faculty Publications and Presentations

Magnetotransport, the response of electrical conduction to external magnetic field, acts as an important tool to reveal fundamental concepts behind exotic phenomena and plays a key role in enabling spintronic applications. Magnetotransport is generally sensitive to magnetic field orientations. In contrast, efficient and isotropic modulation of electronic transport, which is useful in technology applications such as omnidirectional sensing, is rarely seen, especially for pristine crystals. Here a strategy is proposed to realize extremely strong modulation of electron conduction by magnetic field which is independent of field direction. GdPS, a layered antiferromagnetic semiconductor with resistivity anisotropies, supports a field-driven insulator-to-metal transition …

Exploring The Structure Of Space Science Research In Mexico Using Science Mapping Tool: Citespace., Ibis Anette Moreno-Lozano, Humberto Carrillo-Calvet, Jose Luis Jiménez-Andrade, Ricardo Arencibia-Jorge

UTA Libraries Staff Publications - Archive

This paper presents an analysis of the knowledge structure of the Mexican scientific community in the field of Space Science in Web of Science, between 2000 and 2019. CiteSpace software helped to identify the influential papers in the domain. The findings of this study shed light on the historical development of Space Science in Mexico and highlight the country's scientific performance with the worldwide trend. Moreover, the study emphasized the importance of bibliometrics in understanding the scientific undercurrents of a discipline. By analyzing co-citation networks, the study identified prominent clusters and research fronts in the field, providing valuable insights into …

Size And Shape Dependence Of Hydrogen-Induced Phase Transformation And Sorption Hysteresis In Palladium Nanoparticles, Xingsheng Sun, Rong Jin

Chemical and Materials Engineering Faculty Publications

Phase transitions of metals in hydrogen (H) environments are critically import- ant for applications in energy storage, catalysis, and sensing. Nanostructured metallic particles can lead to faster charging and discharging kinetics, increased lifespan, and enhanced catalytic activities. However, establishing a direct causal link between nanoparticle structure and function remains challenging. In this work, we establish a computational framework to explore the atomic config- uration of a metal-hydrogen system when in equilibrium with a H environ- ment. This approach combines Diffusive Molecular Dynamics with an itera- tion strategy, aiming to minimize the system’s free energy and ensure uniform chemical potential across …

Factors Influencing Households’ Willingness To Adopt Rooftop Solar Power In The Philippines, Rosalina Palanca-Tan

Economics Department Faculty Publications

The Philippines is endowed with vast solar potential. Through rooftop solar power (RTSP), households directly participate in the clean energy transition, expanding renewable energy supply to meet increasing energy demand and effectively lowering electricity costs for themselves. Yet, RTSP in the country remains largely untapped. Using the Contingent Valuation framework, this study conducted a survey of households in Metro Manila and its neighboring provinces to identify the factors that influence adoption and willingness to pay for RTSP. Survey results reveal that both economic (mainly electricity bill reduction) and environmental benefits are well-recognized and positively correlated with RTSP adoption. The study …

Perspectives Through The Lens Of Educators And Students: Teaching Flood Mitigation And Other Controversial Food, Energy, Water Nexus Issues In The Classroom, Sumaiya Tabassum

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Science and society are inseparably linked, shaping each other in ways that define our world, emphasizing the need to teach science for empowering students capable of taking meaningful action toward building a sustainable and just society. Developing sustainability competencies in students is an important step toward this goal, with controversial socio-scientific issues (SSIs) providing a valuable teaching context, that encourage students in analyzing interdisciplinary evidence while considering the social, economic impacts of potential solutions. However, recognizing the unique perspectives individuals bring to the classroom is prerequisite for tailoring effective, inclusive instruction, as perspectives often shape learning and classroom-engagement. This study …

Algebraic Structures On Parallelizable Manifolds, Sergey Grigorian

School of Mathematical & Statistical Sciences Faculty Publications

In this paper we explore algebraic and geometric structures that arise on parallelizable manifolds. Given a parallelizable manifold L , there exists a global trivialization of the tangent bundle, which defines a map ρ p : l ⟶ T p L for each point p ∈ L , where l is some vector space. This allows us to define a particular class of vector fields, known as fundamental vector fields, that correspond to each element of l . Furthermore, flows of these vector fields give rise to a product between elements of l and L , which in turn induces …

Angels Or Demons: Investigating And Detecting Decentralized Financial Traps On Ethereum Smart Contracts, Jiachi Chen, Jiang Hu, Xin Xia, David Lo, John Grundy, Zhipeng Gao, Ting Chen

Research Collection School Of Computing and Information Systems

Decentralized Finance (DeFi) uses blockchain technologies to transform traditional financial activities into decentralized platforms that run without intermediaries and centralized institutions. Smart contracts are programs that run on the blockchain, and by utilizing smart contracts, developers can more easily develop DeFi applications. Some key features of smart contracts—self-executed and immutability—ensure the trustworthiness, transparency and efficiency of DeFi applications and have led to a fast-growing DeFi market. However, misbehaving developers can add traps or backdoor code snippets to a smart contract, which are hard for contract users to discover. We call these code snippets in a DeFi smart contract as “DeFi …

Cas: Fusing Dnn Optimization & Adaptive Sensing For Energy-Efficient Multi-Modal Inference, Dulanga Weerakoon, Vigneshwaran Subbaraju, Joo Hwee Lim, Archan Misra

Research Collection School Of Computing and Information Systems

Intelligent virtual agents are used to accomplish complex multi-modal tasks such as human instruction comprehension in mixed-reality environments by increasingly adopting richer, energy-intensive sensors and processing pipelines. In such applications, the context for activating sensors and processing blocks required to accomplish a given task instance is usually manifested via multiple sensing modes. Based on this observation, we introduce a novel Commit-and-Switch ( CAS ) paradigm that simultaneously seeks to reduce both sensing and processing energy. In CAS , we first commit to a low-energy computational pipeline with a subset of available sensors. Then, the task context estimated by this pipeline …

Badfl: Backdoor Attack Defense In Federated Learning From Local Model Perspective, Haiyan Zhang, Xinghua Li, Mengfan Xu, Ximeng Liu, Tong Wu, Jian Weng, Robert H. Deng

Research Collection School Of Computing and Information Systems

There is substantial attention to federated learning with its ability to train a powerful global model collaboratively while protecting data privacy. Despite its many advantages, federated learning is vulnerable to backdoor attacks, where an adversary injects malicious weights into the global model, making the global model's targeted predictions incorrect. Existing defenses based on identifying and eliminating malicious weights ignore the similarity variation of the local weights during iterations in the malicious model detection and the presence of benign weights in the malicious model during the malicious local weight elimination, resulting in a poor defense and a degradation of global model …

Irl For Restless Multi-Armed Bandits With Applications In Maternal And Child Health, Gauri Jain, Pradeep Varakantham, Haifeng Xu, Aparna Taneja, Prashant Doshi, Milind Tambe

Research Collection School Of Computing and Information Systems

Public health practitioners often have the goal of monitoring patients and maximizing patients’ time spent in “favorable” or healthy states while being constrained to using limited resources. Restless multi-armed bandits (RMAB) are an effective model to solve this problem as they are helpful to allocate limited resources among many agents under resource constraints, where patients behave differently depending on whether they are intervened on or not. However, RMABs assume the reward function is known. This is unrealistic in many public health settings because patients face unique challenges and it is impossible for a human to know who is most deserving …