Digital Commons Network^™

Protective Multi-Stressor Interactions In The Anthropocene: Key Considerations For Investigating Cross-Tolerance In A Conservation Context, Essie M Rodgers, Simone Baldanzi, Michael Collins, W Wesley Dowd, Lauric Feugere, Giovanna Mottola, Fanny Vermandele, Daniel F Gomez Isaza

School of Biological and Marine Sciences

In the Anthropocene, species are increasingly faced with multiple stressors that are more severe and less predictable than before. While multiple stressors often interact to affect organisms negatively, sometimes these interactions can be beneficial, enhancing resilience through cross-protection. Cross-protection interactions occur when exposure to one stressor, such as elevated temperature, enhances an organism’s tolerance to a different stressor, like hypoxia, through shared protective mechanisms or signaling pathways. Understanding the potential for cross-protection to combat rapid and diverse environmental change is crucial for conservation, as it potentially alters the predicted consequences of such change. Here, we outline 10 key considerations for …

Selected Prose And Poetry, Ralph Waldo Emerson

Hannah Arendt Marginalia - All

New York, Rinehart [1950]

Call #: PS1602 .C6

Contains light underlining

PDF Information: 18 pages – 797KB

The Prophet Armed: Trotsky, 1879-1921, Isaac Deutscher

Hannah Arendt Marginalia - All

New York : Oxford University Press, 1954.

Call #: DK254.T6 D4

Arendt copy contains marginalia, underlining, marginal lining and endpaper notes

PDF Information: 143 pages – 11.7 MB

Using A Layered Ensemble Of Physics-Guided Graph Attention Networks To Predict Covid-19 Trends, Connie Sun, Vijayalakshmi Kumarasamy, Yu Liang, Dalei Wu, Yingfeng Wang

UTC Spring Research and Arts Conference

The COVID-19 pandemic has rapidly disseminated worldwide, profoundly impacting numerous nations. Accurately forecasting the trajectory of COVID-19 across various scales is crucial for informing public health decisions. However, existing forecasting models primarily operate at the state or country level. Conventional mathematical models face limitations due to oversimplified assumptions, while machine learning algorithms struggle to extrapolate novel trends. This underscores the necessity for hybrid machine learning models that amalgamate domain expertise to enable precise long-term predictions. In response, we propose a sophisticated three-layered ensemble, tailored to geographical insights and fostering extensive peer learning. Our framework aims to forecast COVID-19 trends at …

Machine Learning For Reparameterization Of Molecular Dynamics Water Model To Accurately Capture Electrical And Thermal Behavior, Khowshik Dey, Murat Barisik, Yu Liang

UTC Spring Research and Arts Conference

Water is an important component in many scientific and engineering applications, but precisely modeling its thermal, electrical, and physical properties remains difficult in molecular dynamics (MD) simulations. The widely used TIP4P water model, while useful in many circumstances, requires parameterization to better agreement with experimental results under various conditions. In this study, interpretable machine learning techniques were used to systematically tune the TIP4P model parameters where mathematical relationship between features and targets has been developed using deep symbolic optimization (DSO), resulting in a more accurate depiction of water behavior in molecular dynamics simulation. A data-driven approach was created to optimize …

Assessing The Fidelity Of Ai-Generated Lessons For Elementary-Grades Stem Topics, Deborah Mcallister

UTC Spring Research and Arts Conference

Teachers collaborated using MagicSchool, an AI tool, for generating lesson plans for elementary-grades mathematics, science, and technology topics. The lessons were evaluated for fidelity to content and lesson plan components. The problem to be answered was two-fold: What is the fidelity of AI-generated lessons for elementary-grades STEM topics? What are teacher perceptions of using an AI tool? Teachers evaluated the standards-based, AI-generated lesson plans. Scores for lesson plans were compared by content area (mathematics, science, technology) and elementary level (lower versus upper) to determine if fidelity is better for a particular content area or level. Teacher perceptions, regarding the use …

Modeling The Dynamics Of User Adoption And Abandonment For A Single Product, Uyen Nguyen

UTC Spring Research and Arts Conference

We introduce a compartmental differential equation model to study the dynamics of user adoption and abandonment for a single product. The model integrates two forms of abandonment: infectious, driven by user interactions, and non-infectious, prompted by external influences. Notably, the infectious abandonment coefficient varies linearly with the number of previous users. We investigate the existence of equilibria of the model and derive the threshold quantity ℛ0. The user-free equilibrium is always present, and its stability is analyzed under the condition ℛ0 < 1. Moreover, a user-prevailing equilibrium does not exist when ℛ0 ≤ 1, but at least one user-prevailing equilibrium is guaranteed when ℛ0 > 1. We further characterize conditions for multiple equilibria and various bifurcations, including saddle-node, 𝑆-shaped, and Hopf bifurcations, and formulate …

Risk-Averse Decision-Making In Multiobjective Combinatorial Optimization, Chathuri M. Aththanayake, Lakmali Weerasena

UTC Spring Research and Arts Conference

Uncertainty in input data significantly affects the quality of solutions in mathematical optimization, making it crucial to explore alternative decisions when the selected decision becomes unavailable or suboptimal. This study introduces a novel risk-averse decision-making approach for cases where objective function coefficients are uncertain in multi-objective combinatorial optimization problems. We construct a region in the objective space based on reference solutions obtained from the deterministic formulation. Alternative decisions, identified using a neighboring structure that falls within this region, are used to determine risk-preference solutions. We propose two sets of indices to quantify the quality of outcomes and neighboring decisions in …

Forced Labor In Soviet Russia, David J. Dallin, Boris I. Nikolaevsky

Hannah Arendt Marginalia - All

New Haven, Yale University Press, 1947

Call #: HV8931.R8 D3

contains underlining, marginal lining and endpaper notes (front of book)

PDF information: 35 pages – 3.1 MB

On World-Government, Or De Monarchia, Dante Alighieri

Hannah Arendt Marginalia - All

New York : The Liberal Arts Press, c1957

Call #: PQ 4315.62 .S3 1957

Contains marginalia & underlining

PDF Information: 31 pages – 12 MB

The Philosophical Works Of Descartes Vol. 1, René Descartes

Hannah Arendt Marginalia - All

Cambridge : University Press, 1977 reprinting, c1931

Call #: B1837 .H254 1977

Arendt copy v.1-2 contains underlining, marginal lining and endpaper notes.

PDF Information: 24 pages – 8 MB

Extended-Release Buprenorphine With Bupivacaine Effectively Provides Postoperative Analgesia In A Mouse Laparotomy Model, Monika K. Huss, Amber Kerk, Renee Cotton, Helen Chum, Michael Hsieh, Katechan Jampachaisri, Patrick Sharp, Cholowat Pacharinsak

The Thai Journal of Veterinary Medicine

Multimodal analgesia is widely encouraged for major survival surgery. This facilitates lower doses of individual drugs, thereby reducing side effects. Extended-release analgesics offer sustained analgesia coverage, prevent drug dosing nadirs, and reduce stress. Studies evaluating multimodal and extended-release analgesia combinations for major survival surgery in mice are limited. We compared the analgesic effect of bupivacaine and extended-release buprenorphine (Bupi-ER) to bupivacaine and buprenorphine HCl (Bupi-HCl). We hypothesized that preoperative Bupi-ER would provide more effective analgesia than Bupi-HCl. Mice were randomly assigned to 1 of 2 treatment groups: bupivacaine (2 mg/kg, local infiltration, once) with either 1) extended-release buprenorphine (0.6 mg/kg, …

The Unwritten Philosophy And Other Essays, Francis M. Cornford

Hannah Arendt Marginalia - All

Cambridge: University Press, 1950

Call #: B1618.C763 U5

Contains underlining and marginal lining

PDF Information: 46 pages – 27.7 mb

Plato’S Republic; A Philosophical Commentary, R. C. Cross

Hannah Arendt Marginalia - All

New York, St. Martin’s Press, 1964

Call #: JC71.P6 C68

Contains gift inscription “To Heinrich Bluecher – Margarite Fisher”; also contains marginalia

PDF Information: 30 pages – 1,980KB

Tusculan Disputation, Marcus Tullius Cicero

Hannah Arendt Marginalia - All

Cambridge, Mass., Harvard University Press, 1950

Call #: PA6156.C6 T6 1950

Contains underlining, marginal lining and endpaper notes.

PDF Information: 27 pages – 6 MB

The Rebel, Albert Camus

Hannah Arendt Marginalia - All

New York, Vintage Books, 1956

Call #: HM281 .C3513 1956

Arendt copy contains marginalia, including front and endpaper notes.

PDF Information: 112 pages – 12.9MB

An Essay On Man, Ernest Cassirer

Hannah Arendt Marginalia - All

Garden City, NY: Doubleday, 1953 [c1944]

Call #: B3216.C33 E8 1953

Marginalia , underlining and marginal lining

PDF Information: 14 pages – 4 MB

Substance And Function And Einstein’S Theory Of Relativity, Ernest Cassirer

Hannah Arendt Marginalia - All

New York: Dover Publications, 1953

Call #: BD221 .C3 1953

Contains underlining and endpaper notes, and contained ephemera found between pp. 408-409: a German language newspaper (Nr. 52 Weihnachten 1960).

PDF Information: 18 pages – 8 mb

Retracted: Dynamics And Stability Analysis Of 8-Dimensional Hyperchaotic Systems: Study Of Lyapunov Exponents, Abdulsattar Abdullah Hamad, Nida Muhsin Ali, Muayyad Mahmood Khalil

Iraqi Journal for Computer Science and Mathematics

This research explores the complex dynamics of an 8D hyperchaotic system, focusing on its trajectory stability and behavior under various control parameters. By using numerical simulations, we investigate the relationship between the Lyapunov components and the stability of the system. It provides a quantitative measure of the chaos within the model of the matrix, whose derivation consists of the system's sensitivity to perturbation, simulating chaotic systems in high dimensions faces challenges such as high computational resource demands. Difficulty in ensuring numerical convergence and stability. The results highlight the profound impact of control parameters on the dynamic behavior of hyperchaotic systems. …

Corneal Elevation Maps Patterns Classification Using Correlation Method, Sura M. Ahmed, Nebras H. Ghaeb, Salman Yussof, Noor T. Al-Sharify, Husam Yahya Nser, Zainab T. Al-Sharify, Ong Hang See, Leong Yeng Weng

Iraqi Journal for Computer Science and Mathematics

The ophthalmologist uses various techniques to diagnose corneal abnormalities, including corneal topography and tomography devices. Currently generated color corneal elevation surface maps from topographic imaging devices are essential for detecting ocular diseases, while accurately classifying these maps to differentiate between different shapes remains an issue. This study aims to assess and compare parameters of the front and back corneal surface elevation map patterns of normal/abnormal corneas. Two hundred cases were randomly taken (100 normal and 100 abnormal) with a single normal reference image, and then an additional 25 cases were added later for the optimization process. The preprocessing of all …

Retracted: Comparative Study Based On Continuous Analysis Of Autism Spectrum Disorder Using Advanced Deep Learning With Model Interpretability Insights, Ayan Sar, Hussain Falih Mahdi, Sumit Aich, Pranav Singh, Tanupriya Choudhury

Iraqi Journal for Computer Science and Mathematics

Hysterical conversion has similar cognition and behaviours to those in the case of ASD; it is, therefore, complex when diagnosing and classifying the condition. The majority of employed diagnostic tests are cross-sectional and fail to describe the developmental and clinical features of ASD; for this reason, they are pretty inaccurate in the diagnosis of ASD and thus cause disparities in the efficiency of the therapeutic interventions used. The present study's research contribution is a new application of deep learning that aims to analyse the spectrum of ASD with gradient-based classifications. In this case, we use a DL model trained on …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Computational And In Vitro Investigation Of P. Crocatum Bioactive Compounds As Pancreatic Lipase Inhibitors, Gusnia Meilin Gholam, Dimas Andrianto, Dewi Anggraini Septaningsih, Mega Safithri

Karbala International Journal of Modern Science

Obesity, a prevalent metabolic disorder characterized by excessive fat accumulation, can severely affect overall health if left untreated. This study investigated the potential of a 70% ethanol extract from Piper crocatum (red betel) leaves as an in vitro inhibitor of pancreatic lipase (PL), supported by computational analyses to identify alternative compounds to orlistat. The phytochemical profile was characterized using LC-MS/MS, revealing alkaloids and terpenoids with contents of 1.1 ± 0.01 mg CE/g and 3.14 ± 0.3 mg UAE/g, respectively. The extract exhibited 49 ± 9.1% inhibition of PL activity. Molecular docking identified three promising compounds: calanolide A (10.43 kcal/mol), myricanone …

Professional Learning For Antiracist District Transformation: The Role Of Transformational Leadership And Double-Loop Learning, Patricia Marisol Virella, Chedia Ayari, Steve Tozer

Department of Educational Leadership Scholarship and Creative Works

Introduction: This study investigates how professional learning contributes to antiracist district transformation, focusing on the roles of transformational leadership and double-loop learning. Transformational leadership inspires followers to achieve exceptional goals, while double-loop learning involves questioning underlying assumptions and values to foster systemic change.

Methods: A longitudinal case study approach was employed to examine the experiences of seven district and school-level leaders in an urban-intensive school district. These leaders participated in a multi-year antiracist professional learning series designed to promote equity and systemic change.

Results: Preliminary findings indicate that the professional learning series facilitated a shift in participants’ racial schema and …

Network Intelligence For Next-Generation Wireless Networks: Advancing Distribution And Coordination, Yonatan Melese Worku

Electrical and Computer Engineering ETDs

Next-generation wireless networks, encompassing 6G and beyond, face rigorous demands for ultra-low latency, ubiquitous connectivity, exceptionally high data rates, and robust security, necessitating innovative approaches to resource optimization and network protection. This dissertation proposes a pioneering framework that synergizes advanced methodologies—deep reinforcement learning, deep learning, blockchain, and multi-agent systems—to address these challenges. Distributed architectures, underpinned by AI-driven multi-agent systems, form the backbone of this framework, enabling seamless integration and intelligent orchestration across diverse domains. The research advances IoT-based systems leveraging machine learning for resource efficiency in healthcare applications, develops reinforcement learning-driven frameworks to optimize energy and coverage for Unmanned Aerial …

Classifying Heterogeneous Cooperation In Social Dilemmas: Experimental Evidence And Simulation Insights, Sining Wang

Faculty Scholarship

In this paper, we introduce a revealed strategy method to capture heterogeneous behavioral patterns in repeated public goods experiments. This method identifies an individual’s strategic type—a stable decision-making tendency in interactive settings—by analyzing behavioral profiles. We conduct a repeated public goods game to collect participants’ behavioral data and then apply both k-medians and hierarchical clustering algorithms to classify them into five distinctive types: free riders, strong cooperators, above-average conditional cooperators, below-average conditional cooperators, and hump-shaped players. These classifications are then used to construct and calibrate an agent-based simulation model. Our simulation results suggest that policies targeting how conditional cooperators respond …

2023-01-17 Leadership Council Minutes, Susie Salazar

Executive Council Minutes

No abstract provided.

In Silico Prediction Of Cytotoxic T-Cell Epitopes From Helicobacter Pylori Virulence Factors Using An Immunoinformatics Approach, Demy Valerie Chacon, Kiana Alika Co, Daphne Noreen Enriquez, Aubrey Love Labarda, Reanne Eden Manongsong, Edward Kevin B. Bragais

Biology Faculty Publications

Background: Helicobacter pylori infects approximately half of the global population, leading to gastric and duodenal ulcers. Despite the availability of antibiotics, challenges such as patient reluctance, high treatment costs, and antibiotic resistance limit their effectiveness, making vaccination a promising alternative. This study used immunoinformatics to identify candidate epitopes for a multiepitope vaccine construct against H. pylori.

Material and methods: The protein variability server was utilized for conservation analysis. The epitopes were screened for antigenicity, allergenicity, toxicity, cross-reactivity, and population coverage. Selected epitopes were docked with their corresponding human leukocyte antigen (HLA) alleles, and thermodynamic quantities were determined. Five virulence …

Optimization And Acceleration Of Puf Design Through Reduced Order Standard Cell Modeling, Ian Z. Wilcox

Electrical and Computer Engineering ETDs

Application Specific Integrated Circuit (ASIC) designs continue to scale with ever increasing complexity and device counts in the billions. Demand for scalable high-fidelity simulations of these systems drives the need for the development of novel modeling capabilities. This research formulates a non-intrusive model order reduc-tion (MOR) framework, called PUF-ROMS, to accelerate and optimize the design and analysis of physical unclonable functions (PUFs) on ASICs. The primary goals of PUF-ROMS are to estimate entropy and temperature-voltage noise (TV-noise) of circuit structures used in the design in an accelerated evaluation environment to enable designers to explore architecture options with the goal of …