Digital Commons Network^™

Assessing Tax Revenue Implications Of Environmental Policy: A Case Study Of China’S Channel City Policy, Yongwen Yang, Juhee Lee

School of Earth, Environmental, & Marine Sciences Faculty Publications

Recent studies suggest that while environmental policies yield positive environmental effects, they also incur costs for various entities. However, there is a gap in research regarding these policies’ financial impact from the government's perspective. To investigate the extent to which government tax revenue is affected by environmental policies, we employ the Difference-inDifferences (DID) method to estimate the impact of a regional air pollution control policy in China known as the Channel City Policy on the tax revenue of city governments. Our findings indicate that the Channel City Policy (CCP) enhances air quality by reducing PM2.5, SO2, and NOx concentrations by …

Efficient Hierarchical Contrastive Self-Supervising Learning For Time Series Classification Via Importance-Aware Resolution Selection, Kevin Garcia, Juan M. Perez, Yifeng Gao

Computer Science Faculty Publications

Recently, there has been a significant advancement in designing Self-Supervised Learning (SSL) frameworks for time series data to reduce the dependency on data labels. Among these works, hierarchical contrastive learning-based SSL frameworks, which learn representations by contrasting data embeddings at multiple resolutions, have gained considerable attention. Due to their ability to gather more information, they exhibit better generalization in various downstream tasks. However, when the time series data length is significant long, the computational cost is often significantly higher than that of other SSL frameworks. In this paper, to address this challenge, we propose an efficient way to train hierarchical …

A Simple Proof That Ricochet Robots Is Pspace-Complete, Jose Balanza-Martinez, Angel A. Cantu, Robert Schweller, Tim Wylie

Computer Science Faculty Publications

In this paper, we seek to provide a simpler proof that the relocation problem in Ricochet Robots (Lunar Lockout with fixed geometry) is PSPACE-complete via a reduction from Finite Function Generation (FFG). Although this result was originally proven in 2003, we give a simpler reduction by utilizing the FFG problem, and put the result in context with recent publications showing that relocation is also PSPACE-complete in related models.

Faculty Perceptions Of Online Instruction And Educational Technology In Higher Education, Raul Nick Cabrera, Velma D. Menchaca, Marie Simonsson, Hilda Silva

Organization and School Leadership Faculty Publications

The purpose of this research was to obtain faculty perceptions of online instruction and educational technology in higher education. Data was collected from eight participants through interviews and open-ended questions at a higher education institution. Results showed that faculty consider that online instruction is only possible for certain programs and that it’s only for certain student populations. In addition, faculty perceive online learning environments as a repository for class information and serve as a communication medium between instructor and student. Furthermore, faculty believe that there is no substitution for traditional teaching methods regardless of the educational technology available. Theoretical and …

I Am A Man: Understanding Black Male Identity And Mental Health Needs, Rommel Johnson

School of Rehabilitation Services & Counseling Faculty Publications

Despite the historical and perpetual trauma, racism, discrimination, socio-economical, and socio-political disparities they have experienced in the United States, Black men have consistently forged ways to demonstrate resilience and assert their own sense of autonomy and masculinity. Nevertheless, their ecological context of living in a country that has historically sought to dehumanize them and eradicate their manhood is cumbersome to their mental wellbeing. Furthermore, the tendency by researchers to pathologize Black males obfuscates the reality of their situation in the United States, minimizing their mental needs. Understanding both the complexity of their ecological context as well as their adaptability and …

Qctaas (Quality Cloud Teaching As A Service): An Immersive Framework For Teaching Cloud Computing For Cybersecurity Majors, Mahmoud K. Quweider, Liyu Zhang, Alexis Aaron De La Cruz

Informatics and Engineering Systems Faculty Publications

Abstract Cloud Computing and Cybersecurity are at the heart of our recently created new bachelor-level degree in cybersecurity that addresses the national need for cybersecurity specialists. Cloud Computing involves many service models, including IaaS, PaaS, and SaaS, and many deployment models including Public, Private, and Hybrid clouds. Within the services and deployment models lies many concepts and practical implementations that a Cyber-analyst needs to master. We have adopted an immersive approach to teaching Cloud Computing services that introduces standard concepts based on clearly defined objectives from national certification authorities such as CompTIA Cloud+, covering all major services offered by the …

Neoclassical Production, Scarcity Of Skills And Pareto Distributions, Armando R. Lopez-Velasco

School of Economics and Finance Faculty Publications

The distribution of top earnings follows a “power-law”: the top tail of the distribution is thick relative to other distributions and is approximately Pareto-distributed. There are different mechanisms proposed in the literature that yield Pareto distributions and power-laws. This paper shows that a simple general equilibrium model where aggregate production is assumed of the constant-elasticity-of-substitution (CES) type over multiple labor inputs generates distributions in earnings and wages that follow power-laws. The finding is very general as the distribution of the skill-types is irrelevant for the shape parameter (the Pareto exponent) of the power-law. The model displays a tight relationship between …

Late-Arriving Votes And Electoral Fraud: A Natural Experiment And Regression Discontinuity Evidence From Bolivia, Diego Escobari, Gary A. Hoover

School of Economics and Finance Faculty Publications

This paper uses a unique data set and a natural experiment to test if electoral fraud can exist in late-arriving votes. On the night of the 2019 Bolivian elections, the official vote counting system that was expected to publish the results real-time, suddenly stopped. When it resumed, the results had flipped. We estimate several difference-in-differences specifications using a 2016 referendum and the votes of other political parties. We find that the extent of the fraud is 2.51% of the valid votes, sufficient to change the outcome of the election. Our results are robust to polling-station-level shocks common across 2019 and …

Promoting Understanding Of Three Dimensions Of Science Learning Plus Nature Of Science Using Phenomenon-Based Learning, Maryam Saberi, Noushin Nouri

Teaching and Learning Faculty Publications

The utilization of phenomenon-based learning (PhBL) for science instruction remains limited despite its alignment with the goals outlined in the Next Generation Science Standards (NGSS; NGSS Lead States, 2013) due to the lack of exemplary materials and inadequate training opportunities for teachers. The aim of this article is to illustrate the steps of the PhBL method by providing an exploratory learning experience as it was implemented in a preservice setting. In this study, we provide an innovative perspective by illuminating how this kind of instruction can be used as a context to explicitly discuss the three dimensions of learning (i.e., …

Exploring Integrated Active Learning Practices In An Accelerated Fully Online Graduate-Level Course At A Hispanic Serving Institution, P. Ming-Tsan Lu, Seokmin Kang

Teaching and Learning Faculty Publications

The purpose of the study aimed to explore integrated active learning (IAL) practices in a graduate-level fully online, accelerated course at an HSI, with a focus on students’ perceptions, and to evaluate the implementation of integrated active learning based on student feedback and reflections. Course instructors started implementing IAL practices for the same course in 2022. Data from before and after IAL implementation in terms of course syllabi and course designs on Blackboard, the LMS used in the HSI, were collected. To investigate students’ perceptions, survey methods were also conducted. Findings revealed that graduate students overwhelmingly preferred IAL over traditional …

Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, …

Conditional Constrained And Unconstrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we present the idea of conditional quantization for a Borel probability measure P on a normed space Rk. We introduce the concept of conditional quantization in both constrained and unconstrained scenarios, along with defining the conditional quantization errors, dimensions, and coefficients in each case. We then calculate these values for specific probability distributions. Additionally, we demonstrate that for a Borel probability measure, the lower and upper quantization dimensions and coefficients do not depend on the conditional set of the conditional quantization in both constrained and unconstrained quantization.

Structure Of Fine Selmer Groups In Abelian P-Adic Lie Extensions, Debanjana Kundu, Filippo Alberto Edoardo Nuccio Mortarino Majno Di Capriglio, Sujatha Ramdorai

School of Mathematical & Statistical Sciences Faculty Publications

This paper studies fine Selmer groups of elliptic curves in abelian p -adic Lie extensions. A class of elliptic curves are provided where both the Selmer group and the fine Selmer group are trivial in the cyclotomic Z p -extension. The fine Selmer groups of elliptic curves with complex multiplication are shown to be pseudonull over the trivializing extension in some new cases. Finally, a relationship between the structure of the fine Selmer group for some CM elliptic curves and the Generalized Greenberg's Conjecture is clarified.

Flow And Stability Of Three-Dimensional Rotating Viscoelastic Jet, Daniel N. Riahi

School of Mathematical & Statistical Sciences Faculty Publications

We consider rotationally driven nonlinear viscoelastic jet. In contrast to previous unrealistic planar studies with no gravity effect, we investigate here realistic three-dimensional jet with gravity effect. Using theoretical and computational methods, we develop models for such jet and its stability and determine the solutions. We find three-dimensional jet with gravity effect leads to faster and thinner jet. For jet arc length higher than its exit diameter, our calculation with typical parameter values shows that jet radius is smaller by a factor of more than 1.4 and jet speed is higher by factor of more than 2 as are compared …

Ivermectin, Colleen Aldous, Eleftherios Gkioulekas, Philip Oldfield

School of Mathematical & Statistical Sciences Faculty Publications

No abstract provided.

Enhanced Resolution Method For Electromagnetic Vortex Imaging Based On Electromagnetic Information Theory, Da Liu, Hongyin Shi, Ting Yang, Zhijun Qiao

School of Mathematical & Statistical Sciences Faculty Publications

The electromagnetic vortex imaging possesses independent orbital angular momentum with orthogonal degrees of freedom (DoF), which implies the existence of enhanced information capacity. However, high-mode orbital angular momentum (OAM) beams have stringent generation conditions and inefficient information carrying capacity, which results in limited resolution. This paper proposes a method to combine the electromagnetic information theory (EIT) with the traditional electromagnetic vortex imaging technique, which allows one may obtain more target azimuth information. The DoF, as the main component of information, has been increased to achieve higher azimuth resolution. First, the propagation and imaging model for the electromagnetic vortex with statistical …

Optimizing Energy Consumption In Smart Homes Using Ga-Lstm, Akibor Junior Chukwuka, Bakare-Bolaji Moyosoreoluwa, Baboucarr Dibba

School of Mathematical & Statistical Sciences Faculty Publications

The need to optimize energy consumption arises from the inadequate energy supply many homes face. However, to optimize energy consumption in a home, one must be equipped with the knowledge of the energy consumption rate and energy supply rate in the home. This paper proposed the use of a Long Short-Term Memory (LSTM) model optimized by Genetic Algorithm (GA) to optimize the energy consumption in a smart home. The model was designed using 8 input variables, which were observed weather information of a given region over a span of 350 days. The data set was split into a training data …

Heuristics For Anti-Cyclotomic ℤp-Extensions, Debanjana Kundu, Lawrence C. Washington

School of Mathematical & Statistical Sciences Faculty Publications

This paper studies Iwasawa invariants in anti-cyclotomic towers. We do this by proposing two heuristics supported by computations. First we propose the Intersection Heuristics: these model “how often” the p-Hilbert class field of an imaginary quadratic field intersects the anti-cyclotomic tower and to what extent. Second we propose the Invariants Heuristics: these predict that the Iwasawa invariants 𝜆 and 𝜇 usually vanish for imaginary quadratic fields where p is non-split.

Riemannian Frameworks For The Harmonization Of Resting-State Functional Mri Scans, Nicolas Honnorat, Sudha Seshadri, Ron Killiany, John Blangero, David C. Glahn, Peter T. Fox, Mohamad Habes

School of Medicine Publications

Magnetic Resonance Imaging provides unprecedented images of the brain. Unfortunately, scanners and acquisition protocols can significantly impact MRI scans. The development of statistical methods able to reduce this variability without altering the relevant information in the scans, often coined harmonization methods, has been the topic of an increasing research effort supported by the recent growth of publicly available neuroimaging data sets and new possibilities for combining them to achieve greater statistical power. In this work, we focus on the challenges specifically raised by the harmonization of resting-state functional MRI scans. We propose to harmonize resting-state fMRI scans by reducing the …

Integrating Remote Sensing With Ground-Based Observations To Quantify The Effects Of An Extreme Freeze Event On Black Mangroves (Avicennia Germinans) At The Landscape Scale, Melinda Martinez, Michael J. Osland, James B. Grace, Nicholas M. Enwright, Camille L. Stagg, Camille L. Stagg, Simen Kaalstad, Gordon H. Anderson, Elena A. Flores, Alejandro Fierro-Cabo

School of Earth, Environmental, & Marine Sciences Faculty Publications

Climate change is altering the frequency and intensity of extreme weather events. Quantifying ecosystem responses to extreme events at the landscape scale is critical for understanding and responding to climate-driven change but is constrained by limited data availability. Here, we integrated remote sensing with ground-based observations to quantify landscape-scale vegetation damage from an extreme climatic event. We used ground- and satellite-based black mangrove (Avicennia germinans) leaf damage data from the northern Gulf of Mexico (USA and Mexico) to examine the effects of an extreme freeze in a region where black mangroves are expanding their range. The February 2021 …

Managing Inter-Organizational Trust And Risk Perceptions In Transboundary Fisheries Governance Networks, Evelyn Roozee, Dongkyu Kim, Antonia Sohns, Jasper R. De Vries, Owen Temby, Gordon M. Hickey

School of Earth, Environmental, & Marine Sciences Faculty Publications

Transboundary fishery management represents a significant governance challenge that requires ongoing inter-organizational communication, collaboration, and collective action to ensure sustainability. Previous research suggests that different dimensions of perceived risk, trust, and control interact in complex ways to affect inter-organizational collaborative performance, providing an administrative ‘architecture’ that enables partners to share resources, engage in teamwork, resolve conflict, and coordinate tasks and responsibilities while also allaying their concerns about the alliance. However, the extent to which different control mechanisms influence trust and mitigate the perceived risks of collaboration between the diverse organizations involved in transboundary fisheries management remains unclear. This paper presents …

H-Nobs: Achieving Certified Fairness And Robustness In Distributed Learning On Heterogeneous Datasets, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian

Electrical and Computer Engineering Faculty Publications

Fairness and robustness are two important goals in the design of modern distributed learning systems. Despite a few prior works attempting to achieve both fairness and robustness, some key aspects of this direction remain underexplored. In this paper, we try to answer three largely unnoticed and unaddressed questions that are of paramount significance to this topic: (i) What makes jointly satisfying fairness and robustness difficult? (ii) Is it possible to establish theoretical guarantee for the dual property of fairness and robustness? (iii) How much does fairness have to sacrifice at the expense of robustness being incorporated into the system? To …

Approximating Discrimination Within Models When Faced With Several Non-Binary Sensitive Attributes, Yijun Bian, Yujie Luo, Ping Xu

Electrical and Computer Engineering Faculty Publications

Discrimination mitigation with machine learning (ML) models could be complicated because multiple factors may interweave with each other including hierarchically and historically. Yet few existing fairness measures are able to capture the discrimination level within ML models in the face of multiple sensitive attributes. To bridge this gap, we propose a fairness measure based on distances between sets from a manifold perspective, named as ‘harmonic fairness measure via manifolds (HFM)’ with two optional versions, which can deal with a fine-grained discrimination evaluation for several sensitive attributes of multiple values. To accelerate the computation of distances of sets, we further propose …

Investigating Preservice Teachers’ Conceptualizations Of Mathematical Knowledge For Teaching Through Video Analysis, Bima Sapkota

School of Mathematical & Statistical Sciences Faculty Publications

Mathematics Preservice Teachers’ (M-PSTs) conceptions of Mathematical Knowledge for Teaching (MKT) enhance their reflective skills because they utilize such conceptions to reflect on how to contextualize content knowledge during secondary mathematics teaching. While previous studies suggested M-PSTs develop MKT, including pedagogical content knowledge by analyzing teaching in video lessons, how M-PSTs enhance their conceptions of MKT through such analysis is underexplored. I used a collective case study approach to investigate how four secondary M-PSTs conceptualized MKT when they analyzed and discussed teaching represented in a video lesson using the MKT framework. The findings indicated that the M-PSTs often described teacher …

Use Of Hydroxychloroquine In Multidrug Protocols For Sars-Cov-2, Eleftherios Gkioulekas, Peter A. Mccullough

School of Mathematical & Statistical Sciences Faculty Publications

We review the available evidence supporting the use of hydroxychloroquine-based multidrug protocols in the treatment of COVID-19, in response to a recently published editorial in the Tasman Medical Journal.

Assessing Concepts, Procedures, And Cognitive Demand Of Chatgpt-Generated Mathematical Tasks, Bima Sapkota, Liza Bondurant

School of Mathematical & Statistical Sciences Faculty Publications

In November 2022, ChatGPT, an Artificial Intelligence (AI) large language model (LLM) capable of generating human-like responses, was launched. ChatGPT has a variety of promising applications in education, such as using it as thought-partner in generating curricular resources. However, scholars also recognize that the use of ChatGPT raises concerns, such as outputs that are inaccurate, nonsensical, or vague. We, two mathematics teacher educators, engaged in a collaborative self-study using qualitative descriptive approaches to investigate the procedures, concepts, and cognitive demand of ChatGPT-generated mathematical tasks focused on fraction multiplication using the area model approach. We found that the ChatGPT-generated tasks were …

Brillouin Zones Of Integer Lattices And Their Perturbations, Herbert Edelsbrunner, Alexey Garber, Mohadese Ghafari, Teresa Heiss, Morteza Saghafian, Mathijs Wintraecken

School of Mathematical & Statistical Sciences Faculty Publications

For a locally finite set, 𝐴⊆ℝ𝑑 , the 𝑘 th Brillouin zone of 𝑎∈𝐴 is the region of points 𝑥∈ℝ𝑑 for which ‖𝑥−𝑎‖ is the 𝑘 th smallest among the Euclidean distances between 𝑥 and the points in 𝐴 . If 𝐴 is a lattice, the 𝑘 th Brillouin zones of the points in 𝐴 are translates of each other, and together they tile space. Depending on the value of 𝑘 , they express medium- or long-range order in the set. We study fundamental geometric and combinatorial properties of Brillouin zones, focusing on the integer lattice and its perturbations. Our …

Advancements In Glitch Subtraction Systems For Enhancing Gravitational Wave Data Analysis: A Brief Review, Mohammad Abu Thaher Chowdhury

Physics & Astronomy Faculty Publications

Glitches are transitory noise artifacts that degrade the detection sensitivity and accuracy of interferometric observatories such as LIGO and Virgo in gravitational wave astronomy. Reliable glitch subtraction techniques are essential for separating genuine gravitational wave signals from background noise and improving the accuracy of astrophysical investigations. This review study summarizes the main glitch subtraction methods used in the industry. We talk about the efficacy of classic time-domain techniques in real-time applications, like matched filtering and regression methods. The robustness of frequency-domain approaches, such as wavelet transformations and spectral analysis, in detecting and mitigating non-stationary glitches is assessed. We also investigate …

On Combinatorics Of Voronoi Polytopes For Perturbations Of The Dual Root Lattices, Alexey Garber

School of Mathematical & Statistical Sciences Faculty Publications

The Voronoi conjecture on parallelohedra claims that for every convex polytope P that tiles Euclidean d-dimensional space with translations there exists a d-dimensional lattice such that P and the Voronoi polytope of this lattice are affinely equivalent. The Voronoi conjecture is still open for the general case but it is known that some combinatorial restrictions for the face structure of P ensure that the Voronoi conjecture holds for P. In this article, we prove that if P is the Voronoi polytope of one of the dual root lattices Dd*, E6*, E7* or E8*=E8 or their small perturbations, then every parallelohedron …

Atomically Dispersed Zeolite-Supported Rhodium Complex: Selective And Stable Catalyst For Acetylene Semi-Hydrogenation, Yuxin Zhao, Özge D. Bozkurt, Samira F. Kurtoğlu-Öztulum, Melisa Su Yordanli, Adam S. Hoffman, Jiyun Hong, Jorge E. Perez-Aguilar, Aylin Saltuk, Deniz Akgül, Tülay Ateşin

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Highlights

• Rhodium has heretofore been known to be unselective for acetylene semi-hydrogenation.

• Electronic properties of rhodium are tuned by choice of support and metal nuclearity.

• Selectivity is maximized when Rh is atomically dispersed on a weak electron donor.

• Zeolite-supported Rh complex with C2H2 ligands offers a stable C2H4 selectivity > 90 %.

• Results demonstrate unprecedented catalytic properties of Rh for semi-hydrogenation.

Abstract

Supported rhodium catalysts are known to be unselective for semi-hydrogenation reactions. Here, by tuning the electronic structure of supported mononuclear rhodium sites determined by the metal nuclearity and the electron-donor properties of the support, we report that atomically dispersed …