Digital Commons Network^™

Investigating The Corporate Governance And Sustainability Relationship: A Bibliometric Analysis Using Keyword-Ensemble Community Detection, Carlo Drago, Fabio Fortuna

Fondazione Eni Enrico Mattei Working Papers

Sustainability is a business strategy combining economic, social, and environmental issues. This paper examines the corporate governance and sustainability literature. So we consider a new bibliometric database focusing on the network of keywords appearing in the literature. The quantitative approach is also new: we combine the information from different community detection algorithms to find the most important results and relationships in the literature. The final results show that the literature on corporate governance and sustainability raises an essential strategic question: for long-term sustainability if there needs to be a strong link between stakeholders and corporate social responsibility (CSR). So, considering …

Adversarial Alignment For Source Free Object Detection, Qiaosong Chu, Shuyan Li, Guangyi Chen, Kai Li, Xiu Li

Machine Learning Faculty Publications

Source-free object detection (SFOD) aims to transfer a detector pre-trained on a label-rich source domain to an unlabeled target domain without seeing source data. While most existing SFOD methods generate pseudo labels via a source-pretrained model to guide training, these pseudo labels usually contain high noises due to heavy domain discrepancy. In order to obtain better pseudo supervisions, we divide the target domain into source-similar and source-dissimilar parts and align them in the feature space by adversarial learning. Specifically, we design a detection variance-based criterion to divide the target domain. This criterion is motivated by a finding that larger detection …

Corruption-Tolerant Algorithms For Generalized Linear Models, Bhaskar Mukhoty, Debojyoti Dey, Purushottam Kar

Machine Learning Faculty Publications

This paper presents SVAM (Sequential Variance-Altered MLE), a unified framework for learning generalized linear models under adversarial label corruption in training data. SVAM extends to tasks such as least squares regression, logistic regression, and gamma regression, whereas many existing works on learning with label corruptions focus only on least squares regression. SVAM is based on a novel variance reduction technique that may be of independent interest and works by iteratively solving weighted MLEs over variance-altered versions of the GLM objective. SVAM offers provable model recovery guarantees superior to the state-of-the-art for robust regression even when a constant fraction of training …

Exploring The Genotypic And Phenotypic Differences Distinguishing Lactobacillus Jensenii And Lactobacillus Mulieris, Adriana Ene, Swarnali Banerjee, Alan J. Wolfe, Catherine Putonti

Mathematics and Statistics: Faculty Publications and Other Works

Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, and Lactobacillus jensenii are dominant species of the urogenital microbiota. Prior studies suggest that these Lactobacillus species play a significant role in the urobiome of healthy females. In our prior genomic analysis of all publicly available L. jensenii and Lactobacillus mulieris genomes at the time (n = 43), we identified genes unique to these two closely related species. This motivated our further exploration here into their genotypic differences as well as into their phenotypic differences. First, we expanded genome sequence representatives of both species to 61 strains, including publicly available …

Examination Of Domestic Tourists’ Awareness And Attitude Towards Halal Food According To Demographic Variable: The Gaziantep Example, Adem Ademoglu

Journal of Mediterranean Tourism Research

Religion and belief which are among the intangible cultural elements play an essential role in shaping consumer behavior. Among these behaviors, individuals’ increasing religious sensitivity within the context of eating and drinking in particular necessitates the food they consume to be in concordance with religious values. From this point of view, it is envisioned that individuals’ demographic characteristics will cause differences in food consumption demands in accordance with their religiousness values. The purpose of this study is to determine the role of demographic variables in the awareness towards halal food consumption and attitude towards halal food. Moreover, another purpose of …

Incorporation Of Carbon Dioxide Production And Transport Module Into A Soil-Plant-Atmosphere Continuum Model, Sahila Beegum, Wenguang Sun, Dennis Timlin, Zhuangji Wang, David Fleisher, Vangimalla R. Reddy, Chittaranjan Ray

Nebraska Water Center: Faculty Publications

Carbon dioxide release from agricultural soils is influenced by multiple factors, including soil (soil properties, soil-microbial respiration, water content, temperature, soil diffusivity), plant (carbon assimilation, rhizosphere respiration), atmosphere (climate, atmospheric carbon dioxide), etc. Accurate estimation of the carbon dioxide (CO₂) fluxes in the soil and soil respiration (CO₂ flux between soil and atmosphere) requires a process-based modeling approach that accounts for the influence of all these factors. In this study, a module for CO₂ production via root and microbial respiration and diffusion-based carbon dioxide transport is developed and integrated with MAIZSIM (a process-based maize crop growth …

A Multi-Scale Method For Combined Design And Dispatch Optimization Of Nuclear Hybrid Energy Systems Including Storage, Daniel Hill, Dawson Mccrea, An Ho, Matthew Memmott, Kody Powell, John Hedengren

Faculty Publications

Reliable, carbon-free power generation is increasing in importance. Nuclear-renewable hybrid energy systems (NHES) are a potential solution for current generation challenges, but design and dispatch optimization for these systems remains challenging particularly when stochastic effects, long time horizons and nonlinear modeling are needed. This work presents a multi-scale method for combining the design and dispatch optimization problems for nonlinear NHES over long time horizons. Rather than treating the entire horizon as a single optimization problem, a large number of combined optimization problems are solved for shorter samples of the horizon resulting in distributions of optimal capacities for each of the …

How Do Dispositional Mindfulness And Statistical Anxiety Affect Student Performance On An Exam?, Mario Diaz

Theses and Dissertations

The current study investigated if a specific disposition, mindfulness, offers an advantage for undergraduate students’ success on statistical exams by decreasing the impact of an academic-related strain, anxiety. Prior research utilizing state mindfulness has found evidence of this performance advantage, but it has yet to be investigated if dispositional mindfulness offers similar results. The current study found that dispositional mindfulness does impact one’s anxiety, but that relation does not offer a performance advantage for those with higher levels of mindfulness in comparison to those with lower levels of the disposition. To improve student success, engaging in mindfulness practices appears more …

Acquisition Of A Lexicon For Family History Information: Bidirectional Encoder Representations From Transformers-Assisted Sublanguage Analysis, Liwei Wang, Huan He, Andrew Wen, Sungrim Moon, Sunyang Fu, Kevin J Peterson, Xuguang Ai, Sijia Liu, Ramakanth Kavuluru, Hongfang Liu

Faculty, Staff and Student Publications

BACKGROUND: A patient's family history (FH) information significantly influences downstream clinical care. Despite this importance, there is no standardized method to capture FH information in electronic health records and a substantial portion of FH information is frequently embedded in clinical notes. This renders FH information difficult to use in downstream data analytics or clinical decision support applications. To address this issue, a natural language processing system capable of extracting and normalizing FH information can be used.

OBJECTIVE: In this study, we aimed to construct an FH lexical resource for information extraction and normalization.

METHODS: We exploited a transformer-based method to …

Wildlife Ecological Risk Assessment In The 21st Century: Promising Technologies To Assess Toxicological Effects, Barnett A. Rattner, Thomas G. Bean, Val R. Beasley, Philippe Berny, Karen M. Eisenreich, John E. Elliott, Margaret L. Eng, Phyllis C. Fuchsman, Mason D. King, Rafael Mateo, Carolyn B. Meyer, Jason M. O'Brien, Christopher J. Salice

United States Geological Survey: Staff Publications

Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air‐breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) …

Hydrogen-Bonding Trends In A Bithiophene With 3- And/Or 4-Pyridyl Substituents, Alison M. Costello, Rabekah Duke, Stephanie Sorensen, Nadeesha L. Kothalawala, Moses Ogbaje, Nandini Sarkar, Doo Young Kim, Chad Risko, Sean R. Parkin, Aron J. Huckaba

Chemistry Faculty Publications

To improve the charge-carrier transport capabilities of thin-film organic materials, the intermolecular electronic couplings in the material should be maximized. Decreasing intermolecular distance while maintaining proper orbital overlap in highly conjugated aromatic molecules has so far been a successful way to increase electronic coupling. We attempted to decrease the intermolecular distance in this study by synthesizing cocrystals of simple benzoic acid coformers and dipyridyl-2,2′- bithiophene molecules to understand how the coformer identity and pyridine N atom placement affected solid-state properties. We found that with the 5-(3-pyridyl)-5′-(4-pyridyl)-isomer, the 4- pyridyl ring interacted with electrophiles and protons more strongly. Synthesized cocrystal powders …

Experimental Verification Of Pch-Em Algorithm For Characterizing Dsern Image Sensors, Aaron J. Hendrickson, David P. Haefner, Nicholas R. Shade, Eric R. Fossum

Dartmouth Scholarship

The Photon Counting Histogram Expectation Maximization (PCH-EM) algorithm has recently been reported as a candidate method for the characterization of Deep Sub-Electron Read Noise (DSERN) image sensors. This work describes a comprehensive demonstration of the PCH-EM algorithm applied to a DSERN capable quanta image sensor. The results show that PCH-EM is able to characterize DSERN pixels for a large span of quanta exposure and read noise values. The per-pixel characterization results of the sensor are combined with the proposed Photon Counting Distribution (PCD) model to demonstrate the ability of PCH-EM to predict the ensemble distribution of the device. The agreement …

Flying By Ml Or Cnn Inversion Of Affine Transforms, Lloyd Van Warren

Theses and Dissertations

This dissertation describes how to automate the reading of dials, gauges, and instruments using machine learning (ML) methods. This process can be described as analog to digital conversion through an air gap without any direct electronic connection. The goal is to convert the values of existing instruments into digital values for control and monitoring without requiring any intrusion, changes, or upgrades to the instruments being observed. Images of instrument faces can be distorted by various kinds of noise, but this can be overcome using a deep learning convolutional neural network (CNN) approach similar to handwriting recognition. One advantage of this …

Buffer Effects In Zirconium-Based Uio Metal−Organic Frameworks (Mofs) That Influence Enzyme Immobilization And Catalytic Activity In Enzyme/Mof Biocatalysts, Raneem Ahmad, Sydnie Rizaldo, Mahnaz Gohari, Jordan Shanahan, Sarah E. Shaner, Kari Stone, Daniel S. Kissel

Chemistry Department Faculty Articles

Novel biocatalysts that feature enzymes immobilized onto solid supports have recently become a major research focus in an e!ort to create more sustainable and greener chemistries in catalysis. Many of these novel biocatalyst systems feature enzymes immobilized onto metal−organic frameworks (MOFs), which have been shown to increase enzyme activity, stability, and recyclability in industrial processes. While the strategies used for immobilizing enzymes onto MOFs can vary, the conditions always require a bu!er to maintain the functionality of the enzymes during immobilization. This report brings attention to critical bu!er e!ects important to consider when developing enzyme/MOF biocatalysts, specifically for bu!ering systems …

Continuous Time Dynamic Mode Decomposition In The Presence Of Partial Knowledge And Streaming Data, Efrain H. Gonzalez

USF Tampa Graduate Theses and Dissertations

Dynamic mode decomposition (DMD) is a physically interpretable data driven technique for modeling dynamical systems. The DMD method uses time series data where each data point is referred to as a snapshot and represents the value of the state at a particular moment in time. The important patterns found in the data are extracted and then used to create a model for the system. Once the important pieces have been obtained reduced order modeling can be used to reduce the complexity of the model.

But, DMD has evolved since its inception. After its association with the Koopman operator, DMD has …

Cortex-Wide Neural Dynamics Predict Behavioral States And Provide A Neural Basis For Resting-State Dynamic Functional Connectivity, Somayeh Shahsavarani, David N Thibodeaux, Weihao Xu, Sharon H Kim, Fatema Lodgher, Chinwendu Nwokeabia, Morgan Cambareri, Alexis J Yagielski, Hanzhi T Zhao, Daniel A Handwerker, Javier Gonzalez-Castillo, Peter A Bandettini, Elizabeth M C Hillman

Faculty, Staff and Student Publications

Although resting-state functional magnetic resonance imaging (fMRI) studies have observed dynamically changing brain-wide networks of correlated activity, fMRI's dependence on hemodynamic signals makes results challenging to interpret. Meanwhile, emerging techniques for real-time recording of large populations of neurons have revealed compelling fluctuations in neuronal activity across the brain that are obscured by traditional trial averaging. To reconcile these observations, we use wide-field optical mapping to simultaneously record pan-cortical neuronal and hemodynamic activity in awake, spontaneously behaving mice. Some components of observed neuronal activity clearly represent sensory and motor function. However, particularly during quiet rest, strongly fluctuating patterns of activity across …

Designing A Departmental Program To Improve Belonging And Stem Identity, Teresa J. Bixby, Alec Werner

Chemistry Department Faculty Conferences

Student sense of community and belonging are two key factors that affect student persistence in STEM higher education. On average, nearly half of STEM majors leave their program, most within the first two years of study. To address this at Lewis, strategies from learning communities are being incorporated to provide a sense of community and belonging that may be absent from a typical education experience: community events that provide students with an opportunity to interact outside of the classroom and establish connections, seminar courses that promote STEM identity development and career exploration, and specialized tutoring and mentoring services that build …

Covid-19 And Kidney Disease (Kd): A Retrospective Investigation In A Rural Southwestern Missouri Region Patient Population, Kailey Kowalski, Shilpa Bhat, Mariah Fedje, Nova Beyersdorfer, Darrin S. Goade, Kerry Johnson, Robert Arnce, Robert Hillard

Faculty and Staff Publications

Background: Studies have linked pre-existing kidney disease (KD) to higher rates of mortality due to coronavirus disease 2019 (COVID-19) infection. In the rural Midwest, where KD is prevalent, the impact of COVID-19 has been significant in a population that includes many patients on Medicare or Medicaid.

Methods: A retrospective cohort study was performed assessing patients with acute kidney injury (AKI), chronic kidney disease (CKD) and end stage renal disease (ESRD), with and without COVID-19. International Classification of Diseases 10th Revision codes were submitted by physicians into Freeman Health System’s Electronic Medical Records and gathered from April 2020 to January 2021. …

Waste Treatment Facility Location For Hotel Chains, Dolores R. Santos-Peñate, Rafael R. Suárez-Vega, Carmen Florido De La Nuez

ITSA 2022 Gran Canaria - 9th Biennial Conference: Corporate Entrepreneurship and Global Tourism Strategies After Covid 19

Tourism generates huge amounts of waste. About half of the waste generated by hotels is food and garden bio-waste. This bio-waste can be used to make compost and pellets. In turn, pellets can be used as an absorbent material in composters and as an energy source. We consider the problem of locating composting and pellet-making facilities so that the bio-waste generated by a chain of hotels can be managed at or close to the generation points. An optimization model is applied to locate the facilities and allocate the waste and products, and several scenarios are analysed. The study shows that, …

Instagram Travel Influencers Coping With Covid-19 Travel Disruption, Andrei Kirilenko, Katarzyna Emin, Karen Tavares

ITSA 2022 Gran Canaria - 9th Biennial Conference: Corporate Entrepreneurship and Global Tourism Strategies After Covid 19

A significant portion of today’s marketing is done through social media influencers, that is, through bloggers with established online credibility in a certain area who are recognized and followed by a sizable online audience. In the travel and hospitality industry, the influencer marketing is primarily done through Instagram due to its emphasis on visual images rather than texts. Covid-19 related travel restrictions and shrinking social media advertisement in travel industry have heavily impacted travel influencers, reducing their income and forcing many out of business. We present the outcomes of a study of the top 150 online travel influencers. The analysis …

Reco.Ai: Using Generative Pre-Trained Transformer 3 Model For A Chatbot In Answering Grade 10 Mathematics Questions, Prince Travis S. Amado, Lhord Cedrick T. Delos Santos, Misxa Bien D. Germino, Aaron Gabriel G. Nolo, Vincent Ace C. Fronteras, Robyn Lauren C. Tria, Kent Patrick T. Congreso, Dalziel Oriol

DLSU Senior High School Research Congress

Over the years, several studies have explored AI's ability in terms of education. This study aims to investigate how ReCo.ai performs in terms of accuracy in answering mathematical concepts about Grade 10 Mathematics. Using the Generative Pre-trained Transformer 3 (GPT-3) model to create a chatbot specifically within the grade 10 Mathematics curriculum, and used the GPT-3 Generated Text dataset for machine learning and natural language processing. The researchers tested the accuracy by evaluating its accuracy, precision and recall, and F1 score. F1 score test was used as a performance metric to evaluate the precision and recall of the chatbot's responses. …

Teacher Preparedness And Implementation Of The National Pre-Tertiary Education Curriculum Framework In Ghana, Simon Ntumi, Sheilla Agbenyo, Alex Tetteh, Clarke Ebow Yalley, Abraham Yeboah, Daniel Gyapong Nimo

Journal of Educational Research and Practice

Curriculum reform is a significant approach to prepare schools to be effective in meeting contemporary societal needs and imperatives. Several countries around the world, therefore, engage in curriculum reform to enable schools to prepare children with the knowledge, skills, and competencies needed in the present and future society, but implementing change following a curriculum reform is often complex. In our study, we sought to understand how teachers respond to curriculum implementation following the introduction of the national pre-tertiary education curriculum framework (NPECF) in Ghana. We employed a concurrent, nested, mixed-design strategy (embedded design) using a sample of 352 randomly selected …

Graphprompt: Graph-Based Prompt Templates For Biomedical Synonym Prediction, Hanwen Xu, Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Bhalerao, Yucong Liu, Dawei Zhu, Sheng Wang

Computer Vision Faculty Publications

In the expansion of biomedical dataset, the same category may be labeled with different terms, thus being tedious and onerous to curate these terms. Therefore, automatically mapping synonymous terms onto the ontologies is desirable, which we name as biomedical synonym prediction task. Unlike biomedical concept normalization (BCN), no clues from context can be used to enhance synonym prediction, making it essential to extract graph features from ontology. We introduce an expert-curated dataset OBO-syn encompassing 70 different types of concepts and 2 million curated concept-term pairs for evaluating synonym prediction methods. We find BCN methods perform weakly on this task for …

Biological Case Against Downlisting The Whooping Crane And For Improving Implementation Under The Endangered Species Act, Andrew J. Caven, Hillary L. Thompson, David M. Baasch, Barry K. Hartup, Amanda M. Hegg, Stephanie M. Schmidt, Irvin Louque, Craig R. Allen, Carter G. Crouch, Craig A. Davis, Joel G. Jorgensen, Jane E. Austin, Bethany L. Ostrom, Richard D. Beilfuss, George W. Archibald, Anne E. Lacy

School of Natural Resources: Faculty Publications

The Whooping Crane (Grus americana; WHCR) is a large, long-lived bird endemic to North America. The remnant population migrates between Aransas National Wildlife Refuge, USA, and Wood Buffalo National Park, Canada (AWBP), and has recovered from a nadir of 15-16 birds in 1941 to ~540 birds in 2022. Two ongoing reintroduction efforts in Louisiana and the Eastern Flyway together total ~150 birds. Evidence indicates the U.S. Fish and Wildlife Service (USFWS) is strongly considering downlisting the species from an endangered to a threatened status under the Endangered Species Act (ESA). We examined the current status of the WHCR through the …

Benerd Review - June 2023, Benerd College

Benerd Review

No abstract provided.

Stability-Based Generalization Analysis For Mixtures Of Pointwise And Pairwise Learning, Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang

Machine Learning Faculty Publications

Recently, some mixture algorithms of pointwise and pairwise learning (PPL) have been formulated by employing the hybrid error metric of “pointwise loss + pairwise loss” and have shown empirical effectiveness on feature selection, ranking and recommendation tasks. However, to the best of our knowledge, the learning theory foundation of PPL has not been touched in the existing works. In this paper, we try to fill this theoretical gap by investigating the generalization properties of PPL. After extending the definitions of algorithmic stability to the PPL setting, we establish the high-probability generalization bounds for uniformly stable PPL algorithms. Moreover, explicit convergence …

Class-Independent Regularization For Learning With Noisy Labels, Rumeng Yi, Dayan Guan, Yaping Huang, Shijian Lu

Computer Vision Faculty Publications

Training deep neural networks (DNNs) with noisy labels often leads to poorly generalized models as DNNs tend to memorize the noisy labels in training. Various strategies have been developed for improving sample selection precision and mitigating the noisy label memorization issue. However, most existing works adopt a class-dependent softmax classifier that is vulnerable to noisy labels by entangling the classification of multi-class features. This paper presents a class-independent regularization (CIR) method that can effectively alleviate the negative impact of noisy labels in DNN training. CIR regularizes the class-dependent softmax classifier by introducing multi-binary classifiers each of which takes care of …

Skin Permeation Studies Of Chromium Species - Evaluation Of A Reconstructed Human Epidermis Model., L Hagvall, M Munem, M Hoang Philipsen, M Dowlatshahi Pour, Yolanda S. Hedberg, P Malmberg

Chemistry Publications

A reconstructed human epidermis (RHE) model, the EpiDerm, was investigated and compared to human skin ex vivo regarding tissue penetration and distribution of two chromium species, relevant in both occupational and general exposure in the population. Imaging mass spectrometry was used in analysis of the sectioned tissue. The RHE model gave similar results compared to human skin ex vivo for skin penetration of Cr

A Conceptual Review Of Sustainable Development Goal 17: Picturing Politics, Proximity And Progress, Joanna Stanberry, Janis Bragan Balda

International Business and Entrepreneurship Faculty Publications

We outline the discursive origins of United Nations Sustainable Development Goal (SDG) 17, describing its ambiguous marching orders, which are further confused by shifting and contested stakeholder approaches. The widespread effect is to obscure the primary aim of making the tropics and other vulnerable countries more resilient, and also globally overcoming barriers to their development. We argue that ecological reflexivity, as developed and advanced by deliberative democracy and the Earth System Governance Project, belongs at the apex of those capacities needed for implementing the Agenda for Transformation. Ecological reflexivity conceptually grounds inclusive, open, critical, and consequential engagement of discourses situated …

Friction And Heat Transfer Modeling Of The Tool And Workpiece Interface In Friction Stir Welding Of Aa 6061-T6 For Improved Simulation Accuracy, Ryan Melander

Theses and Dissertations

Friction stir welding (FSW) is a solid-state joining process that offers advantages over traditional fusion welding. The amount of heat generated during a FSW process greatly influences the final properties of the weld. The heat is generated through two main mechanisms: friction and plastic deformation, with friction being the larger contributor in a FSW process. There is a need to develop better predictive models of the heat generation and heat transfer in FSW. Almost all models seen in the literature validate temperature predictions on only one side of the tool/workpiece interface, thus ignoring possible inaccuracy that comes from incorrect partitioning …