Digital Commons Network^™

Pseudomonas Aeruginosa Gene Pa4880 Encodes A Dps-Like Protein With A Dps Fold, Bacterioferritin-Type Ferroxidase Centers, And Endonuclease Activity, Nimesha Rajapaksha, Huili Yao, Aisha Cook, Steve Seibold, Lijun Liu, Kevin P. Battaile, Leo Fontenot, Fabrizio Donnarumma, Scott Lovell, Mario Rivera

Faculty Publications

We report the biochemical, structural, and functional characterization of the protein coded by gene PA4880 in the P. aeruginosa PAO1 genome. The PA4880 gene had been annotated as coding a probable bacterioferritin. Our structural work shows that the product of gene PA4880 is a protein that adopts the Dps subunit fold, which oligomerizes into a 12-mer quaternary structure. Unlike Dps, however, the ferroxidase di-iron centers and iron coordinating ligands are buried within each subunit, in a manner identical to that observed in the ferroxidase center of P. aeruginosa bacterioferritin. Since these structural characteristics correspond to Dps-like proteins, we term the …

The Role Of Holistic Mentoring Ecosystems In Mitigating Covid-19 Pandemic Impacts On The Persistence Of Low-Income Stem Students, Raeshan D. Davis, Zakiya S. Wilson-Kennedy

Faculty Publications

Holistic mentoring ecosystems are a comprehensive approach to addressing the diverse needs of students through interconnected support networks. While mentoring has been well-documented in existing literature, more research is needed to determine the effectiveness of mentoring ecosystems in mitigating the impact of critical junctures for vulnerable, high-attrition student populations. Guided by Tinto’s model of retention, this qualitative case study investigated the role of holistic mentoring ecosystems in mitigating the impacts of the two combined critical junctures—the COVID-19 pandemic and the first year of college—on low-income STEM undergraduates. Our findings suggest that holistic mentoring ecosystems were essential in helping students adjust …

Modelling And Simulation Of The Cholesteric Landau-De Gennes Model, Andrew L. Hicks, Shawn W. Walker

Faculty Publications

This paper discusses modelling and numerical issues in the simulation of the Landau-de Gennes (LdG) model of nematic liquid crystals (LCs) with cholesteric effects. We propose a fully implicit, (weighted) L2 gradient flow for computing energy minimizers of the LdG model, and note a time-step restriction for the flow to be energy decreasing. Furthermore, we give a mesh size restriction, for finite-element discretizations, that is critical to avoid spurious numerical artifacts in discrete minimizers, particularly when simulating cholesteric LCs that exhibit 'twist.' Furthermore, we perform a computational exploration of the model and present several numerical simulations in three dimensions, on …

Protecting A Cornerstone Constitutional Right In The Age Of Zoom: The History And Case Law Surrounding The Confrontation Clause, Laura Anne Rose

Faculty Publications

As the legal field moves into the post-COVID-19 pandemic world, it is essential to evaluate the place virtual meeting software holds in the criminal justice trial system.  This article traces the historical roots of the Confrontation Clause, considers the Supreme Court jurisprudence on the topic with special emphasis on Crawford v. Washington and Maryland v. Craig, traces the circuit split on the use of two-way video communication in criminal trials, and concludes with a review of state cases where the protections of the Confrontation Clause are evaluated with the use of Zoom testimony.

Politicians The Founders Warned You About, Neil Fulton

Faculty Publications

Many articles have explored the Founders' intentions regarding the constitutional text. Much less attention has focused on the Founders' ideas regarding the traits needed of the leaders in a constitutional republic. The Constitution focuses on governing structures, many of which relate to the electoral process. The Constitution does not spell out the ideal traits of the leaders elected pursuant to those processes. Nonetheless, the Founders possessed clear views about the virtues and qualifications that ideal political leaders required. Indeed, the Founders issued warnings about certain archetypal political figures who, because of their flagrant disregard of the ideal virtues and qualifications, …

Do Universities Meet Their Democratic Obligations?, Neil Fulton

Faculty Publications

No abstract provided.

Monitoring Of Wave, Current, And Sediment Dynamics Along The Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland, Hongqing Wang, Qin Chen, William D. Capurso, Lukasz M. Niemoczynski, Nan Wang, Ling Zhu, Gregg A. Snedden, Matt Whitbeck, Carol A. Wilson, Michael Brownley

Faculty Publications

Living shorelines with salt marsh species, rock breakwaters, and sand nourishment were built along the coastal areas in the Glenn Martin National Wildlife Refuge, Maryland, in 2016 in response to Hurricane Sandy (2012). The Fog Point living shoreline at Glenn Martin National Wildlife Refuge was designed with the “headland - breakwater - embayment” pattern. Scientists from the U.S. Geological Survey, Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University studied wave, current, and sediment dynamics to assess the effectiveness of the Fog Point living shoreline structures in terms of wave attenuation and erosion reduction. Wave gages, current meters, …

Dpal-Bert: A Faster And Lighter Question Answering Model, Lirong Yin, Lei Wang, Zhuohang Cai, Siyu Lu, Ruiyang Wang, Ahmed Alsanad, Salman A. Alqahtani, Xiaobing Chen, Zhengtong Yin, Xiaolu Li, Wenfeng Zheng

Faculty Publications

Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems. However, with the constant evolution of algorithms, data, and computing power, the increasing size and complexity of these models have led to increased training costs and reduced efficiency. This study aims to minimize the inference time of such models while maintaining computational performance. It also proposes a novel Distillation model for PAL-BERT (DPAL-BERT), specifically, employs knowledge distillation, using the PAL-BERT model as the teacher model to train two student models: DPAL-BERT-Bi and DPAL-BERT-C. This research enhances the dataset through techniques such as masking, …

Convolution-Transformer For Image Feature Extraction, Lirong Yin, Lei Wang, Siyu Lu, Ruiyang Wang, Youshuai Yang, Bo Yang, Shan Liu, Ahmed Alsanad, Salman A. Alqahtani, Zhengtong Yin, Xiaolu Li, Xiaobing Chen, Wenfeng Zheng

Faculty Publications

This study addresses the limitations of Transformer models in image feature extraction, particularly their lack of inductive bias for visual structures. Compared to Convolutional Neural Networks (CNNs), the Transformers are more sensitive to different hyperparameters of optimizers, which leads to a lack of stability and slow convergence. To tackle these challenges, we propose the Convolution-based Efficient Transformer Image Feature Extraction Network (CEFormer) as an enhancement of the Transformer architecture. Our model incorporates E-Attention, depthwise separable convolution, and dilated convolution to introduce crucial inductive biases, such as translation invariance, locality, and scale invariance, into the Transformer framework. Additionally, we implement a …

Afbnet: A Lightweight Adaptive Feature Fusion Module For Super-Resolution Algorithms, Lirong Yin, Lei Wang, Siyu Lu, Ruiyang Wang, Haitao Ren, Ahmed Alsanad, Salman A. Alqahtani, Zhengtong Yin, Xiaolu Li, Wenfeng Zheng

Faculty Publications

At present, super-resolution algorithms are employed to tackle the challenge of low image resolution, but it is difficult to extract differentiated feature details based on various inputs, resulting in poor generalization ability. Given this situation, this study first analyzes the features of some feature extraction modules of the current super-resolution algorithm and then proposes an adaptive feature fusion block (AFB) for feature extraction. This module mainly comprises dynamic convolution, attention mechanism, and pixel-based gating mechanism. Combined with dynamic convolution with scale information, the network can extract more differentiated feature information. The introduction of a channel spatial attention mechanism combined with …

Intellectual Property And The Myth Of Nonrivalry, James Y. Stern

Faculty Publications

The concept of rivalry is central to modern accounts of property. When one person’s use of a resource is incompatible with another’s, a system of rights to determine its use may be necessary. It is commonly asserted, however, that informational goods like inventions and expressive works are nonrivalrous and that intellectual property rights must therefore be subject to special limitation, if they should even exist at all.

This Article examines the idea of rivalry more closely and makes a series of claims about the analysis of rivalrousness for purposes of such arguments. Within that framework, it argues that rivalry should …

Naming, Expressive Interests, And The Law: The Implications Of Governmental Form Design, Laura A. Heymann

Faculty Publications

The design of governmental forms can result in restrictions on the ability of individuals to submit truthful personal naming choices, such as when a form field has character limitations or does not accept diacritics. In some instances, form design operationalizes government policy. But in other instances, form design can itself create law by limiting the ability to submit accurate names on the front end. Awareness of the legal implications of form design is critically important. A more inclusive and accurate approach toward the legal documentation of naming choices means that forms should adapt to people, not the other way around.

Tarnished Gold: The Endangered Species Act At 50, Jonathan H. Adler

Faculty Publications

This Article aims to take stock of the [Endangered Species Act] ESA’s success and failures during its first fifty years, particularly with regard to the conservation of species habitat on private land. While the ESA authorizes powerful regulatory tools for species conservation, there are serious questions as to whether such tools are the most effective means of conserving species and the habitats on which they rely. Given that most species rely upon private land for their survival, the ESA’s ability to foster private land conservation will affect the law’s overall success.

This abstract has been taken from the author's introduction.

Immediate Repeated Reading Has Positive Effects On Reading Rate For English Language Learners: An Eye-Tracking Study, Jennifer Hemmert Hansen, Grant Eckstein, Troy L. Cox, Steven G. Luke, Krista Rich

Faculty Publications

Fluent and skillful reading in English requires efficient and automatic letter and word recognition. Dysfluent reading can affect motivation for reading in English language learners, thereby limiting access to a wealth of language input from written texts. Extensive research of repeated reading in first language (L1) settings has been shown to increase reading rate, while comparatively little research has been done on repeated reading in second language (L2) settings. The objective of this eye-tracking study was to accurately document early and late reading processes in an immediate repeated reading exercise to observe how repeated reading affects reading rate in adult …

Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang

Faculty Publications

The advent of Urban Air Mobility (UAM) has necessitated a paradigm shift in aircraft design from traditional regression methods to physics-based analysis and the use of modern computational methods. This paper explores the intricacies of UAM aircraft design, acknowledging the limitations of historical empirical equations and advocating for the use of physics-based tools in the early stages of the design process. It underscores the importance of Multidisciplinary Design, Analysis, and Optimization (MDAO) as a means to integrate physics-based tools for conceptual design, facilitating decisions on configuration and sizing. The paper presents a comprehensive survey and review of computational models across …

No-Poach Agreements: An Overview Of Us, Eu, And National Case Law, Donald J. Polden

Faculty Publications

The United States, European Union, and many other international jurisdictions have antitrust and competition laws that seek to prevent anticompetitive conduct concerning labor and employment relationships. However, for many years these prohibitions on restraints of trade in labor markets and employment relationships were not routinely and rigorously enforced by those jurisdictions. The lack of governmental attention to these labor market practices has changed in important ways in recent years. Across many jurisdictions, we are now seeing more intense attention to conduct that suppresses wages of workers and their freedom of job mobility to other comparable positions. From an international perspective, …

Negotiating Quotidian Justice In The Science Classroom, Christopher Irwin, Joshua Ellis

Faculty Publications

In this conceptual paper, we explore how science teachers might enact social justice through their everyday science instruction. Drawing on empirical literature and our own K-12 teaching experience, we develop a heuristic for mapping classroom discourses to engage in action and reflection to change both the world of the classroom community, and the world beyond the school. We suggest how this heuristic can be used for justice-oriented science teaching independently of (or as a supplement to) any existing frameworks for science teaching to promote social justice. Our proposed model for social justice through disciplinary science teaching frames justice not as …

Gender Difference On Internal Equity: Evidence From The Hospitality Industry In Ghana, Patricia Peprah

Faculty Publications

It is a hypothetical position that employees in the hospitality industry in Ghana experience salary disparities based on the gender of the employee. Pay disparities exist because of unconscious biases in areas such as hiring, promotions, performance reviews, and salary decisions. In ensuring equal pay for equal work to fulfill the International Labor Organization (ILO) convention, this study investigated the internal equity pay of the employees in Ghana's hospitality industry based on equal work. This quantitative association study adopted a self-constructed research instrument to measure internal equity pay and randomly selected 350 respondents in the hospitality industry in Ghana to …

Empowering Causal Machine Learning For Large-Scale Manufacturing Pipelines With Knowledge Graphs, Yuxin Zi, Cory Henson, Amit P. Sheth

Faculty Publications

Understanding causal relations within manufacturing pipelines is crucial for key manufacturing tasks such as anomaly detection and root cause analysis. However, existing causal machine learning (causal ML) approaches struggle to scale effectively to the vast number of variables present in manufacturing settings. We advocate for incorporating domain knowledge within the manufacturing pipelines, represented as knowledge graphs (KGs), for designing causal ML methods for large-scale manufacturing problems. Knowledge graphs can encode rich contextual information about the interactions and dependencies between different components and stages of the manufacturing pipeline, providing a structured framework to guide the discovery of causal relationships. By incorporating …

Summer-Wet Hydrologic Cycle During The Middle Miocene Of The United States: New Evidence From Fossil Fungi, Jennifer M.K. O’Keefe, Matthew J. Pound, Ingrid C. Romero, Noelia B. Nuñez Otaño, Martha E. Gibson, Jessica Mccoy, Margaret E. Alden, C. Jolene Fairchild, Julia Fitzpatrick, Emily Hodgson, Taylor Horsfall, Savannah Jones, June E. Lennex-Stone, Christopher A. Marsh, Alyssa A. Patel, Tyler M. Spears, Laikin Tarlton, Liberty F. Smallwood, O. L. Vanderespt, Jeremyah R. Cabrera, Cortland F. Eble, William C. Rember, James E. Starnes, Mac H. Alford, Alyson Brink, Sophie Warny

Faculty Publications

Hydrologic reconstructions from North America are largely unknown for the Middle Miocene. Examination of fungal palynomorph assemblages coupled with traditional plant-based palynology permits delineation of local, as opposed to regional, climate signals and provides a baseline for study of ancient fungas. Here, the Fungi in a Warmer World project presents paleoecology and paleoclimatology of 351 fungal morphotypes from 3 sites in the United States: the Clarkia Konservat-Lagerstätte site (Idaho), the Alum Bluff site (Florida), and the Bouie River site (Mississippi). Of these, 83 fungi are identified as extant taxa and 41 are newly reported from the Miocene. Combining new plant-based …

Accelerating L-Shaped Two-Stage Stochastic Scuc With Learning Integrated Benders Decomposition, Fouad Hasan, Amin Kargarian

Faculty Publications

Benders decomposition is widely used to solve large mixed-integer problems. This article takes advantage of machine learning and proposes a variant of Benders decomposition to tackle two-stage stochastic security-constrained unit commitment (SCUC). The problem is decomposed into a master problem (MP) and subproblems (SPs) corresponding to individual load scenarios. The primary objective is to mitigate computational expenses and memory consumption associated with Benders decomposition by generating tighter cuts and reducing the MP's dimensions. A regressor reads load profile scenarios and predicts objective function proxy values for the SPs, enabling the creation of tighter cuts for the MP. The numerical difference …

Optimizing Privacy And Utility Tradeoffs For Group Interests Through Harmonization, Bishwas Mandal, George Amariucai, Shuangqing Wei

Faculty Publications

We propose a novel problem formulation to address the privacy-utility tradeoff, specifically when dealing with two distinct user groups characterized by unique sets of private and utility attributes. Unlike previous studies that primarily focus on scenarios where all users share identical private and utility attributes and often rely on auxiliary datasets or manual annotations, we introduce a collaborative data-sharing mechanism between two user groups through a trusted third party. This third party uses adversarial privacy techniques with our proposed data-sharing mechanism to internally sanitize data for both groups and eliminates the need for manual annotation or auxiliary datasets. Our methodology …

Communication-Efficient Admm Using Quantization-Aware Gaussian Process Regression, Aldo Duarte, Truong X. Nghiem, Shuangqing Wei

Faculty Publications

In networks consisting of agents communicating with a central coordinator and working together to solve a global optimization problem in a distributed manner, the agents are often required to solve private proximal minimization subproblems. Such a setting often requires a decomposition method to solve the global distributed problem, resulting in extensive communication overhead. In networks where communication is expensive, it is crucial to reduce the communication overhead of the distributed optimization scheme. Gaussian processes (GPs) are effective at learning the agents' local proximal operators, thereby reducing the communication between the agents and the coordinator. We propose combining this learning method …

Initial Exploration Of Zero-Shot Privacy Utility Tradeoffs In Tabular Data Using Gpt-4, Bishwas Mandal, George Amariucai, Shuangqing Wei

Faculty Publications

We investigate the application of large language models (LLMs), specifically GPT-4, to scenarios involving the tradeoff between privacy and utility in tabular data. Our approach entails prompting GPT-4 by transforming tabular data points into textual format, followed by the inclusion of precise sanitization instructions in a zero-shot manner. The primary objective is to sanitize the tabular data in such a way that it hinders existing machine learning models from accurately inferring private features while allowing models to accurately infer utility-related attributes. We explore various sanitization instructions. Notably, we discover that this relatively simple approach yields performance comparable to more complex …

The Economics Of Privacy And Utility: Investment Strategies, Chandra Sharma, George Amariucai, Shuangqing Wei

Faculty Publications

The inevitable leakage of privacy as a result of unrestrained disclosure of personal information has motivated extensive research on robust privacy-preserving mechanisms. However, existing research is mostly limited to solving the problem in a static setting with disregard for the privacy leakage over time. Unfortunately, this treatment of privacy is insufficient in practical settings where users continuously disclose their personal information over time resulting in an accumulated leakage of the users' sensitive information. In this paper, we consider privacy leakage over a finite time horizon and investigate optimal strategies to maximize the utility of the disclosed data while limiting the …

Performance Optimization Of Software-Defined Industrial Internet-Of-Things (Sd-Iiot), Jehad Ali, Celestine Iwendi, Gaoyang Shan, Hsiao Chun Wu, Mohammed J.F. Alenazi, Zaid Bin Faheem, Cresantus N. Biamba

Faculty Publications

Software-Defined Networking (SDN) offers a centralized network management approach that can effectively address the complex and varied traffic demands characteristic of Industrial Internet of Things (IIoT) environments by decoupling the control plane from the data plane. The centralized control architecture of SDN necessitates the performance optimization of controllers to manage diverse traffic efficiently within IIoT applications. This paper explores the criteria for selecting controllers in SDN-enabled IIoT (SD-IIoT) environments, utilizing the Less Complex Analytic Network Process (LC-ANP) to establish their prioritization. A ranking system for SD-IIoT controllers is formulated using LC-ANP, and experimental validation of this method underscores its effectiveness …

Tensor Z -Transform, Shih Yu Chang, Hsiao Chun Wu

Faculty Publications

The multi-input multioutput (MIMO) systems involving multirelational signals generated from distributed sources have been emerging as the most generalized model in practice. The existing work for characterizing such a MIMO system is to build a corresponding transform tensor, each of whose entries turns out to be the individual z-transform of a discrete-time impulse response sequence. However, when a MIMO system has a global feedback mechanism, which also involves multirelational signals, the aforementioned individual z-transforms of the overall transfer tensor are quite difficult to formulate. Therefore, a new mathematical framework to govern both feedforward and feedback MIMO systems is in crucial …

Fractal Surface Recovery And Self-Healing Contributed To Sustainable Superhydrophobicity: A Review, Yunfei Peng, Zhihang Ma, Xiao Wang, Junru Li, Xinlin Li, Chuanwei Zhang, Tian He, Guoqiang Li, Pengfei Zhang

Faculty Publications

The concept of superhydrophobicity has been widely used after years of theoretical and experimental exploration. Researchers have obtained materials with excellent surface superhydrophobicity for numerous areas (e.g. textiles, paints, and coatings industries), through different design and synthesis methods using low surface energy components (LSECs) and micro/nanohierarchy composite structures. However, the durability of superhydrophobic material surfaces has gradually become a prominent obstacle to restricting applications. In this paper, advances in improving the durability of superhydrophobic surfaces in the past decade are reviewed, covering different schemes for recovering fractal surfaces based on the LSECs and micro/nanocomposite structures. It also presents a balanced …

Electrical Energy Harvesting By Connected Form Stable Phase Change Material Composites, Chengbin Yu, Guoqiang Li

Faculty Publications

Over the years, thermoelectric energy harvesting has been becoming a topic of intensive research and thermoelectric power generator has been utilized in various energy harvesting applications. However, a thermoelectric device is required to harvest energy, which has relatively low efficiency and high cost. To overcome such a common problem, the objective of this study is to generate electrical energy without using thermoelectric devices. To this end, an advanced energy harvester composed of two different phase change material composites was explored. It was hypothesized that based on the well-known Seebeck effect, stable electrical energy output would be feasible without a thermoelectric …

Fracture Conductivity Management To Improve Heat Extraction In Enhanced Geothermal Systems, Qitao Zhang, Arash Dahi Taleghani, Guoqiang Li

Faculty Publications

The efficiency of an enhanced geothermal reservoir (EGS) depends on the effective circulation of the working fluid through the geothermal formation. To remove the thermal shortcut that leads to thermal short-circuiting in the EGS, we present a method of fracture hydraulic conductivity management and present some practical ways to implement it in the field. The core idea is to correlate the flow resistance in different flow channels with temperature, in order to make uniform heat extraction through each flow path. The presented technique is an adaptive and reversible system and is trying to engineer the fracture system for effective delay …