Digital Commons Network^™

Wastewater Treatment Plants: The Missing Link In Global One-Health Surveillance And Management Of Antibiotic Resistance, Abdolmajid Gholizadeh, Mehdi Khiadani, Maryam Foroughi, Hadi Alizade Siuki, Hadi Mehrfar

Research outputs 2022 to 2026

Introduction: As a global public health crisis, antibiotic resistance (AR) should be monitored and managed under the One-Health concept according to the World Health Organization (WHO), considering the interconnection between humans, animals, and the environment. But this approach often remains focused on human health and rarely on the environment and its compartments, especially wastewater as the main AR receptor. Wastewater treatment plants (WWTPs) not only are not designed for reliving AR but also provide appropriate conditions for enhancing AR through different mechanisms. Methods: By reviewing the research-based statistics on the inclusion of WWTPs in the One-Health/AR program crisis, this paper …

Intersectionalities In Internationalization Studies: An Overview Of Brazilian Research, Simone M. Costa, Lauro Sérgio M. Pereira, Kléber A. Silva

Journal of Comparative & International Higher Education

Special Issue

A Critical Analysis Of The Fulbright Program From A World Systems Perspective, Marisa Lally, Shadman Islem

Journal of Comparative & International Higher Education

No abstract provided.

Multi-Scale Mapping Of Australia’S Terrestrial And Blue Carbon Stocks And Their Continental And Bioregional Drivers, Lewis Walden, Oscar Serrano, Mingxi Zhang, Zefang Shen, James Z. Sippo, Lauren T. Bennett, Damien T. Maher, Catherine E. Lovelock, Peter I. Macreadie, Connor Gorham, Anna Lafratta, Paul S. Lavery, Luke Mosley, Gloria M. S. Reithmaier, Jeffrey J. Kelleway, Sabine Dittmann, Fernanda Adame, Carlos M. Duarte, John B. Gallagher, Pawel Waryszak, Paul Carnell, Sabine Kasel, Nina Hinko-Najera, Rakib Hassan, Madeline Goddard, Alice R. Jones, Raphael A. Viscarra Rossel

Research outputs 2022 to 2026

The soil in terrestrial and coastal blue carbon ecosystems is an important carbon sink. National carbon inventories require accurate assessments of soil carbon in these ecosystems to aid conservation, preservation, and nature-based climate change mitigation strategies. Here we harmonise measurements from Australia’s terrestrial and blue carbon ecosystems and apply multi-scale machine learning to derive spatially explicit estimates of soil carbon stocks and the environmental drivers of variation. We find that climate and vegetation are the primary drivers of variation at the continental scale, while ecosystem type, terrain, clay content, mineralogy and nutrients drive subregional variations. We estimate that in the …

Ethical Considerations For Artificial Intelligence In Educational Assessments, Lim Ming Soon Tristan, Gottipati Swapna, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

In the vital context of education, the application of artificial intelligence (AI) to assessments necessitates a nuanced examination of the boundaries between ethically permissible and impermissible practices. In this chapter, the authors applied a systematic literature mapping methodology to scour extant research, so as to holistically structure the landscape into explicit topical research clusters. Through topic modelling and network analyses, research mapped key ethical principles to different assessment phases in a triadic ontological framework. The chapter looks to provide researchers and practitioners the insights into the ethical challenges that exist across an end-to-end assessment pipeline.

Butte Priority Soils Operable Unit Uncontrolled Surface Flow Areas Draft Remedial Design Work Plan (Rdwp), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Uncontrolled Surface Flow Areas Pre-Design Investigation Work Plan, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Bpsou 2023 Uncontrolled Surface Flow Area Soil Characterization Quality Assurance Project Plan (Qapp), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Butte Treatment Lagoons (Btl) Groundwater Treatment System Routine Operations, Maintenance, And Monitoring (Om&M) Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Constraining Silicate Weathering During The Middle Eocene Climatic Optimum (Meco) Using Radiolarian Ge/Si, Olivia R. Laub

All Graduate Theses and Dissertations, Fall 2023 to Present

Silicate weathering has long been considered a fundamental component of the earth system and has been cited as one of, if not the primary stabilizing feedback for climate. However, recent work has shown that the role of silicate weathering in the climate system is more complicated and dynamic than previously assumed. In this study I examine the role of weathering in the enigmatic warming event, the Middle Eocene Climatic Optimum (MECO) that occurred approximately 40 Ma. This event works as a good case study as there are multiple features of the MECO that differentiate it from other warming events that …

Characterization Of The Long-Distance Dispersal Kernel Of White-Tailed Deer And Evaluating Its Impact On Chronic Wasting Disease Spread In Wisconsin, Mennatallah Gouda

All Graduate Theses and Dissertations, Fall 2023 to Present

Chronic Wasting Disease (CWD) is a fatal, untreatable neurodegenerative disease that infects deer and related species. It is highly contagious and caused by abnormal malfunction and assembly of normal cellular proteins into aggregation-prone proteins. The Centers for Disease Control and prevention report that the prevalence of CWD in free-ranging deer in the US is still relatively low. However, in several states the infection rates exceed 1 deer in 10. Deer may uptake CWD from direct interaction with infected individuals or from the environment. Infected individuals shed CWD into the environment through feces, urine, saliva or carcasses, and long-distance dispersal of …

Student Reliance On Simulations: The Extent That Engineering Students Rely On The Outcomes Of Their Simulations, Jonathan Anderson

All Graduate Theses and Dissertations, Fall 2023 to Present

The purpose of this research was to investigate the factors that contributed to engineering education students’ reliance on technology while learning new concepts. The researcher hypothesized that students would give reliance to their technology, even in the face of evidence that the technology was not working as intended. This research used a mixed-methods approach to answer the research questions. Three questions guided the research: (1) How are the participant’s level of automation complacency and the correctness of the simulation that participant is using related?; (2) How is automation bias related to a participant’s ability to recognize errors in a simulation?; …

Computational Study About Noncovalent Bonding Systems Involving Halogen, Chalcogen And Pnicogen Bonds, Jia Lu

All Graduate Theses and Dissertations, Fall 2023 to Present

First terms used in this thesis are introduced and defined as follows. In the periodic table, the elements in the 17^th column are named halogen including fluorine (F), chlorine (Cl), bromine (Br) and iodine (I). The elements in the 16^th column are named chalcogen including oxygen (O), sulfur (S), selenium (Se) and tellurium (Te). The elements in the 15^th column are named pnicogen including nitrogen (N), phosphorus (P), arsenic (As) and antimony (Sb).

After hydrogen bonds (B-H⋅⋅⋅B) are well studied and understood by scientists and researchers, halogen bonds (R-X⋅⋅⋅B) have drawn attention due to the similarities in …

The Caboose By A Longshot: Impact Of Large Age Gaps On Youngest Siblings, Kelly Clark Young

All Graduate Theses and Dissertations, Fall 2023 to Present

Siblings play a large role in developmental experiences and views of oneself. However, most research addressing siblings looks at individuals who grow up close in age with their siblings. What is currently known about sibling relationships does not seem to fit for those who have siblings but are not close in age to them, referred to in this study as a sibling age gap.

To learn more about what it was like to grow up with siblings who are much older, I interviewed 11 individuals who were the youngest siblings in their family and five or more years younger than …

Did Arroyo Formation Impact The Occupation Of Snake Rock Village, A Fremont Dryland Agricultural Community In Central Utah, Ca. Ad 1000–1200?, Alexandra Wolberg

All Graduate Theses and Dissertations, Fall 2023 to Present

Fremont farmers of the northern Colorado Plateau grew maize at the limits for cultivation in western North America between AD 300–1300. Like other Indigenous farmers throughout the American Southwest, Fremont farmers used bundled agricultural niches where alluvial floodplains were the largest available site for cultivation. But dryland floodplains are a risk to the persistence of farming communities because the development of steep-sided arroyos lowers floodplain surfaces and water tables, rendering them unusable for growing maize. This study tests the relationship between the occupational timing of Snake Rock Village between AD 970–1240 and the formation of a 4.5m deep arroyo on …

Adversarially Reweighted Sequence Anomaly Detection With Limited Log Data, Kevin Vulcano

All Graduate Theses and Dissertations, Fall 2023 to Present

In the realm of safeguarding digital systems, the ability to detect anomalies in log sequences is paramount, with applications spanning cybersecurity, network surveillance, and financial transaction monitoring. This thesis presents AdvSVDD, a sophisticated deep learning model designed for sequence anomaly detection. Built upon the foundation of Deep Support Vector Data Description (Deep SVDD), AdvSVDD stands out by incorporating Adversarial Reweighted Learning (ARL) to enhance its performance, particularly when confronted with limited training data. By leveraging the Deep SVDD technique to map normal log sequences into a hypersphere and harnessing the amplification effects of Adversarial Reweighted Learning, AdvSVDD demonstrates remarkable efficacy …

Co2 Storage Capacity And Injectivity Of Stacked Carbonates Of The Pennsylvanian And Permian In Western Nebraska, Lateef Lawal

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Geological carbon storage (GCS) is a critical aspect of carbon capture and storage (CCS) in which captured CO₂ from power plants and industrial processes is injected and stored securely underground. Potential subsurface rock formations include saline aquifers, depleted oil and gas reservoirs, unmineable coal seams and volcanic rocks. GCS technology has been proven in the United States and many other parts of the world as a net-zero carbon emission strategy to mitigate the current climate crisis of our planet. Unlike other states such as Wyoming, GCS projects are still in the early phases in Nebraska. The goal of this …

Characterization Of Interlayer Laser Shock Peening During Fused Filament Fabrication Of Polylactic Acid (Pla), Fabien Denise

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

The field of additive manufacturing (AM) has gained a significant amount of popularity due to the increasing need for more sustainable manufacturing techniques and the adaptive development of complex product geometries. The problem is that AM parts routinely exhibit flaws or weaknesses that affect functionality or performance. Over the years, surface treatments have been developed to compensate certain flaws or weaknesses in manufactured products. Combining surface treatments with the modularity of additive manufacturing could lead to more adaptable and creative improvements of product functions in the future. The current work evaluates the feasibility of pursuing a new research axis in …

Enhanced Privacy-Enabled Face Recognition Using Κ-Identity Optimization, Ryan Karl

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Facial recognition is becoming more and more prevalent in the daily lives of the common person. Law enforcement utilizes facial recognition to find and track suspects. The newest smartphones have the ability to unlock using the user's face. Some door locks utilize facial recognition to allow correct users to enter restricted spaces. The list of applications that use facial recognition will only increase as hardware becomes more cost-effective and more computationally powerful. As this technology becomes more prevalent in our lives, it is important to understand and protect the data provided to these companies. Any data transmitted should be encrypted …

The Federal Reserve's Mandates, David T. Zaring, Jeffery Y. Zhang

Articles

Solutions to systemic problems such as climate change and racial inequities have eluded policymakers for decades. In searching for creative solutions, some policymakers have recently thought about expanding the Federal Reserve’s core set of macroeconomic mandates to tackle these issues. But there are real questions about whether that can be done from a legal perspective and whether that should be done from a policy perspective.

Factors Predicting Mathematics Achievement In Pisa: A Systematic Review, Xiaofang S. Wang, Laura B. Perry, Anabela Malpique, Tobias Ide

Research outputs 2022 to 2026

The Programme for International Student Assessment (PISA) has become the world’s largest comparative assessment of academic achievement. While hundreds of studies have examined the factors predicting student achievement in PISA, a comprehensive overview of the main predictors has yet to be completed. To address this gap, we conducted a systematic literature review of factors predicting mathematics performance in PISA. Guided by Bronfenbrenner’s ecological model of human development, we synthesized the findings of 156 peer reviewed articles. The analysis identified 135 factors that fall into five broad categories: individual student, household context, school community, education systems and macro society. The analysis …

Global Dataset Of Soil Organic Carbon In Tidal Marshes, Tania L. Maxwell, André S. Rovai, Maria F. Adame, Janine B. Adams, José Álvarez-Rogel, William E. N. Austin, Kim Beasy, Francesco Boscutti, Michael E. Böttcher, Tjeerd J. Bouma, Richard H. Bulmer, Annette Burden, Shannon A. Burke, Saritta Camacho, Doongar R. Chaudhary, Gail L. Chmura, Margareth Copertino, Grace M. Cott, Christopher Craft, John Day, Carmen B. De Los Santos, Lionel Denis, Weixin Ding, Joanna C. Ellison, Carolyn J. E. Lewis, Luise Giani, Maria Gispert, Swanne Gontharet, José A. González-Pérez, M. Nazaret González-Alcaraz, Connor Gorham, Anna E. L. Graversen, Anthony Grey, Roberta Guerra, Qiang He, James R. Holmquist, Alice R. Jones, José A. Juanes, Brian P. Kelleher, Karen E. Kohfeld, Dorte Krause-Jensen, Anna Lafratta, Paul S. Lavery, Edward A. Laws, Carmen Leiva-Dueñas, Pei S. Loh, Catherine E. Lovelock, Carolyn J. Lundquist, Peter I. Macreadie, Inés Mazarrasa, J. Patrick Megonigal, Joao M. Neto, Juliana Nogueira, Michael J. Osland, Jordi F. Pagès, Nipuni Perera, Eva-Maria Pfeiffer, Thomas Pollmann, Jacqueline L. Raw, María Recio, Ana C. Ruiz-Fernández, Sophie K. Russell, John M. Rybczyk, Marek Sammul, Christian Sanders, Rui Santos, Oscar Serrano, Matthias Siewert, Craig Smeaton, Zhaoliang Song, Carmen Trasar-Cepeda, Robert R. Twilley, Marijn Van De Broek, Stefano Vitti, Livia V. Antisari, Baptiste Voltz, Christy N. Wails, Raymond D. Ward, Melissa Ward, Jaxine Wolfe, Renmin Yang, Sebastian Zubrzycki, Emily Landis, Lindsey Smart, Mark Spalding, Thomas A. Worthington

Research outputs 2022 to 2026

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this …

Covariance-Based Causal Debiasing For Entity And Relation Extraction, Lin Ren, Yongbin Liu, Yixin Cao, Chunping Ouyang

Research Collection School Of Computing and Information Systems

Joint entity and relation extraction tasks aim to recognize named entities and extract relations simultaneously. Suffering from a variety of data biases, such as data selection bias, and distribution bias (out of distribution, long-tail distribution), serious concerns can be witnessed to threaten the model’s transferability, robustness, and generalization. In this work, we address the above problems from a causality perspective. We propose a novel causal framework called covariance and variance optimization framework (OVO) to optimize feature representations and conduct general debiasing. In particular, the proposed covariance optimizing (COP) minimizes characterizing features’ covariance for alleviating the selection and distribution bias and …

A Comprehensive Evaluation Of Large Language Models On Legal Judgment Prediction, Ruihao Shui, Yixin Cao, Xiang Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4’s law evaluation raise questions concerning their performance in real-world legal tasks. To systematically investigate their competency in the law, we design practical baseline solutions based on LLMs and test on the task of legal judgment prediction. In our solutions, LLMs can work alone to answer open questions or coordinate with an information retrieval (IR) system to learn from similar cases or solve simplified multi-choice questions. We show that similar cases and multi-choice options, namely label candidates, included in prompts …

Ensemble-Based Deep Reinforcement Learning For Vehicle Routing Problems Under Distribution Shift, Yuan Jiang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jie Zhang

Research Collection School Of Computing and Information Systems

While performing favourably on the independent and identically distributed (i.i.d.) instances, most of the existing neural methods for vehicle routing problems (VRPs) struggle to generalize in the presence of a distribution shift. To tackle this issue, we propose an ensemble-based deep reinforcement learning method for VRPs, which learns a group of diverse sub-policies to cope with various instance distributions. In particular, to prevent convergence of the parameters to the same one, we enforce diversity across sub-policies by leveraging Bootstrap with random initialization. Moreover, we also explicitly pursue inequality between sub-policies by exploiting regularization terms during training to further enhance diversity. …

Metabox: A Benchmark Platform For Meta-Black-Box Optimization With Reinforcement Learning, Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Zhenrui Li, Guojun Peng, Yue-Jiao Gong, Yining Ma, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Recently, Meta-Black-Box Optimization with Reinforcement Learning (MetaBBO-RL) has showcased the power of leveraging RL at the meta-level to mitigate manual fine-tuning of lower-level black-box optimizers. However, this field is hindered by the lack of a unified benchmark. To fill this gap, we introduce MetaBox, the first benchmark platform expressly tailored for developing and evaluating MetaBBO-RL methods. MetaBox offers a flexible algorithmic template that allows users to effortlessly implement their unique designs within the platform. Moreover, it provides a broad spectrum of over 300 problem instances, collected from synthetic to realistic scenarios, and an extensive library of 19 baseline methods, including …

Attack Prompt Generation For Red Teaming And Defending Large Language Models, Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, Xiangnan He

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are susceptible to red teaming attacks, which can induce LLMs to generate harmful content. Previous research constructs attack prompts via manual or automatic methods, which have their own limitations on construction cost and quality. To address these issues, we propose an integrated approach that combines manual and automatic methods to economically generate high-quality attack prompts. Specifically, considering the impressive capabilities of newly emerged LLMs, we propose an attack framework to instruct LLMs to mimic human-generated prompts through in-context learning. Furthermore, we propose a defense framework that fine-tunes victim LLMs through iterative interactions with the attack framework …

Large Language Models As Source Planner For Personalized Knowledge-Grounded Dialogues, Hongru Wang, Minda Hu, Yang Deng, Rui Wang, Fei Mi, Weichao Wang, Yasheng Wang, Wai-Chung Kwan, Irwin King, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Open-domain dialogue system usually requires different sources of knowledge to generate more informative and evidential responses. However, existing knowledge-grounded dialogue systems either focus on a single knowledge source or overlook the dependency between multiple sources of knowledge, which may result in generating inconsistent or even paradoxical responses. To incorporate multiple knowledge sources and dependencies between them, we propose SAFARI, a novel framework that leverages the exceptional capabilities of large language models (LLMs) in planning, understanding, and incorporating under both supervised and unsupervised settings. Specifically, SAFARI decouples the knowledge grounding into multiple sources and response generation, which allows easy extension to …

Wsdms: Debunk Fake News Via Weakly Supervised Detection Of Misinforming Sentences With Contextualized Social Wisdom, Ruichao Yang, Wei Gao, Jing Ma, Hongzhan Lin, Zhiwei Yang

Research Collection School Of Computing and Information Systems

In recent years, we witness the explosion of false and unconfirmed information (i.e., rumors) that went viral on social media and shocked the public. Rumors can trigger versatile, mostly controversial stance expressions among social media users. Rumor verification and stance detection are different yet relevant tasks. Fake news debunking primarily focuses on determining the truthfulness of news articles, which oversimplifies the issue as fake news often combines elements of both truth and falsehood. Thus, it becomes crucial to identify specific instances of misinformation within the articles. In this research, we investigate a novel task in the field of fake news …

Exgen: Ready-To-Use Exercise Generation In Introductory Programming Courses, Nguyen Binh Duong Ta, Hua Gia Phuc Nguyen, Gottipati Swapna

Research Collection School Of Computing and Information Systems

In introductory programming courses, students as novice programmers would benefit from doing frequent practices set at a difficulty level and concept suitable for their skills and knowledge. However, setting many good programming exercises for individual learners is very time-consuming for instructors. In this work, we propose an automated exercise generation system, named ExGen, which leverages recent advances in pre-trained large language models (LLMs) to automatically create customized and ready-to-use programming exercises for individual students ondemand. The system integrates seamlessly with Visual Studio Code, a popular development environment for computing students and software engineers. ExGen effectively does the following: 1) maintaining …