Physical Sciences and Mathematics Commons^™

Designing, Integrating, And Evaluating Blockchain Assignments In The Undergraduate Computer Science Program, Karol Lejmbach

Dissertations (1934 -)

Blockchains as a technology rely heavily on a wide range of computer science topics. These topics include: algorithms, data structures, network communication, cryptography and many more. These topics align nicely with topics often covered in undergraduate computer science course. Blockchain technology offers an interesting opportunity for computer science educa- tors. Blockchains rely heavily on a wide range of computer science topics. These topics include: cryptography, networking, data structures, and algorithms. Many of these top- ics are explored in undergraduate computer science programs either in core or elective classes. This offers an opportunity for teaching students about emerging technologies, such as …

Impacts Of Climate Change On Agricultural Production And Adaptation Strategies In Northeast China, Ming Jiang, Aizhen Liang, Peng Qi

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the “stabilizer” of national food security, Northeast China is highly sensitive to climate change. Over the past 60 years, the regional temperature has risen significantly at a rate of 0.034℃/a, which is much higher than the global average of 0.0074℃/a. The improvement of thermal resources has driven a significant northward expansion of high-yield and heat-demanding crops, such as maize and rice. Nevertheless, increased warming has enhanced evapotranspiration demand, which, combined with the expansion of planting scales, has led to a 19.8% increase in agricultural irrigation water consumption over the past 20 years, resulting in a prominent contradiction between supply …

Impact And Countermeasures Of Climate Change On Grain Production In Northwest China, Qin’Ge Dong, Jianqiang He, Yi Li, Ning Yao, Xiang Li, Haolei Zhang, Shengnan Wang, Tengcong Jiang, Baiqing Chen, Chunrui Gao, Chao Liang, Guiyuan Zhang, Lei Gong, Jinxuan Zhao, Qiang Yu, Hao Feng

Bulletin of Chinese Academy of Sciences (Chinese Version)

Global climate change is reshaping the agricultural production patterns of grain crops in Northwest China. As an important reserve region for national grain production, Northwest China faces multiple uncertainties and compound risks in food security. This study analyzes the current status and limiting factors of grain production, along with regional climate change trends, and systematically evaluates the impacts of climate change and its associated disasters on the spatial distribution, cropping systems, and yield formation of major crops such as wheat, maize, and potato. Over the past 60 years, the region has experienced a warming rate of approximately 0.32℃ per decade …

Strategic Talent Management In Era Of Intelligence And Digitalization: Current Situation And Path Exploration, Chaoying Tang, Chunyuan Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The report of the 20th National Congress of the Communist Party of China emphasized “speed up efforts to build a contingent of personnel with expertise of strategic importance” to support China’s pursuit of high-level technological self-reliance and its goal of becoming a world-leading power in science and technology. The deep integration of digital and intelligent technologies is fundamentally transforming talent management paradigms and innovation processes, posing new demands on the knowledge structure, competency models, and management approaches of strategic talents. The study explores the concepts of strategic talent management in the digital intelligent era, establishes its logical framework, analyzes current …

Risks And Challenges Under Approaching Climate Tipping Points And Governance Recommendations, Chengdong Huang, Xiaohong Chen, Zhifang Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

Climate tipping points represent critical thresholds at which Earth’s climate subsystems undergo abrupt transitions, characterized by irreversibility, self-perpetuation, and complex interconnections, posing severe challenges to global climate governance. This study systematically elucidates the scientific implications and key features of climate tipping points, with a focus on analyzing the multifaceted risks triggered by their activation, including climatic physical risks, socio-economic systemic risks, and national security risks. To address these challenges, the research proposes a governance framework centered on “preventing abrupt changes—maintaining resilience—actively adapting”, emphasizing pathways such as enhanced monitoring and early warning, cultivating new quality productive forces, and constructing a global …

Reading The Room: A Structural Account Of Constraint-Based Processing And Its Limits In Artificial Systems, Griselda Poe

Publications and Research

This paper does not introduce a new structure.

It makes explicit a structural relation implied but not directly stated in prior work.

Human interpersonal processing is grounded in the co-presence of internal constraint and dependency.

These do not exist as separable components.

They form a single structural condition.

This paper shows that what is commonly described as “reading the room” is not a unitary function.

It differs across configurations in how this condition is processed.

In EF configurations, the effect of this condition is expressed through translation into self-return: outputs are evaluated in terms of how they return to the …

Extreme Cf: A Structural Account Of Processing Absence And Category Absence In Cf-Foregrounded Configurations, Griselda Poe

Publications and Research

Existing frameworks of cognition and intervention assume that processing occurs, meaning is available, and evaluation can be applied.

This paper describes a configuration in which this assumption does not hold.

In CF-foregrounded processing where modulation is absent, processing occurs only when coherence is satisfied. When coherence is not satisfied, processing does not occur. Under this condition, no representation is generated, no evaluation applies, and no action selection is produced.

Within single-layer cognitive models, EF and CF are not distinguished. Within such models, CF does not exist as a condition.

This configuration has not been represented as a category within existing …

Fairhiveframes-1k: A Public Fair Dataset Of 1265 Annotated Hive Frame Images With Preliminary Yolov8 And Yolov11 Baselines, Vladimir Kulyukin, Reagan Hill, Aleksey Kulyukin

Computer Science Faculty and Staff Publications

In precision apiculture, the portable digital camera is a cost-effective sensor for capturing hive images or videos used to quantify different colony variables. Openly accessible, well-annotated, interoperable cell-level image datasets are still the exception rather than the norm. This shortage constitutes a major barrier to AI-driven approaches aimed at automating image-based comb analysis. In this article, we present FAIRHiveFrames-1K, a publicly available dataset of 1265 annotated hive frame images (1920 × 1080 PNG) designed to facilitate research in AI-intensive image-based comb analysis automation. The dataset, derived from a 2013–2022 U.S. Department of Agriculture–Agricultural Research Service multi-sensor research reservoir, includes 124,669 …

The Digital Neuron: Neural Cellular Automata For Neural–Symbolic Translation, Nicole Assenza

SMU Data Science Review

A neural cellular automata (NCA) architecture, referred to as Pluto’s NCA, was developed to characterize bilateral communication and semantic reciprocity between symbolic representations and a spatially distributed update field. The architecture employs an encoder–automata–decoder pipeline that maps symbolic inputs into a multichannel state field and reconstructs them through agreement-driven attractor convergence within a stable semantic attractor landscape. System behavior was evaluated under controlled perturbations, including rhythmic desynchronization, graded ablations, correlated and independent noise, and percolation-based structural degradation. Quantities such as Agreement(t), internal coherence Aᵢ(t), the recovery time constant τ, and the critical percolation threshold pc were measured to assess stability, …

Organic Synthesis Of A Hydrazine Functionalized Ammonium Compound For Improved Capture Of Aldehyde Metabolites From Exhaled Breath, Po'iu N. Burgo

Undergraduate Theses

Breath analysis has emerged as a non-invasive and inexpensive way to screen for respiratory diseases. This technique involves measuring concentrations of specific metabolites found in exhaled breath that serve as a biomarkers for disease. A subclass of volatile organic compounds called α,β-Unsaturated aldehydes, products of the lipid peroxidation mechanism, are underrepresented as biomarkers of lung cancer. These have been found to have relatively increased concentrations in the exhaled breath of lung cancer patients compared to a healthy patient. One of the reasons that these metabolites have been underreported is that the techniques used to measure and characterized exhaled metabolites do …

Techno-Enviro-Economic Analysis Of Precipitated Calcium Carbonate Production From Carbon Dioxide In Cement Industry Flue Gas And Calcium Hydroxide, Natalia Debora Panggabean, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

CCUS is a technological solution to reduce emissions from the cement industry, which is the second largest CO2-intensive industry. This study aims to analyze technical, economic, and environmental performance of Precipitated Calcium Carbonate (PCC) synthesis in cement industry flue gas. The process simulation includes the CO2 capture system from cement plant, CO2 captured used as feedstock for PCC synthesis process through its reaction with calcium hydroxide. The simulation was carried out using ASPEN Plus software. Technical analysis was performed to determine the CO2 capture efficiency and PCC synthesis efficiency. Economic analysis was conducted to calculate CO2 capture cost and production …

Feasibility Analysis Of Thermal Oxidizer To Determine Remaining Life Using Fitness- For-Service Level 3 Method, Yudhi Yudistirawan, Donanta Dhaneswara, Wahyuaji Narottama Putra, Gama Widyaputra, Dewi Kurnia Suci, Agung Putra Mahardhika

Journal of Materials Exploration and Findings

An aged thermal oxidizer (TOX) in the oil and gas industry necessitates a comprehensive evaluation to ensure its continued safe operation. This study presents a Remaining Life Assessment (RLA) and a Fitness for Service (FFS) evaluation for the four main components of the TOX, in accordance with API 510, API 579/ASME FFS-1, and ASME BPVC Section VIII Div-1 standards. The investigation includes the determination of maximum stress and maximum temperature required to assess the operational viability of the reactor. The four components are radiant, convection, transition, and stack sections—were modeled using the finite element method (FEM). Following the geometric modeling, …

Assessing Passenger Electric Vehicle Growth Strategies And Their Impacts On Electricity Demand Load And Co2 Emissions In Aceh Province To Achieve Net Zero Emission Target By 2060, Taufik Hidayat, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

The electrification of the transport sector is a crucial pathway for achieving Indonesia’s Net Zero Emissions (NZE) target by 2060. This study assesses the potential impact of passenger electric vehicle (EV) penetration on electricity demand and CO2 emissions in Aceh Province through a scenario-based modelling approach. Two policy-aligned scenarios are assessed: a low-penetration (LP) scenario and a high-penetration (HP) scenario. Using the Gompertz model and the ASIF framework, total CO2 emissions were projected from 2020 to 2060. Results show that although higher EV penetration reduces direct emissions from internal combustion engine (ICE) vehicles, total CO2 emissions increase more significantly under …

Phishing Restraint: University Simulated Phishing Campaigns, Alexander M. Abou Khir

Cybersecurity Undergraduate Research Showcase

Universities face heightened vulnerability to phishing attacks due to their open information-sharing culture and diverse user populations. This study examines how phishing exploits human factors within campus environments and evaluates three major training strategies: embedded phishing, microlearning, and role-based instruction to understand their individual and combined effectiveness. I explored studies that implement these strategies in pairs and use the strategies alone, identified trends in susceptibility reduction, behavioral reinforcement, and contextual relevance. I suggest that, while each method independently improves user awareness, multiple approaches offer stronger, more adaptable protection by addressing both psychological triggers and role-specific risks. The paper contributes a …

Hijacking The Prompt: A Survey Of Prompt Injection Attacks, Detection, And Defense In Large Language Models, Edward J. Griggs

Cybersecurity Undergraduate Research Showcase

Prompt injection attacks, ranked the number-one vulnerability in AI systems by OWASP's 2025 Top 10 for Large Language Model Applications, remain largely unsolved, and this survey examines why. As large language models (LLMs) are deployed across enterprise workflows, agentic systems, and consumer tools, their fundamental inability to distinguish trusted instructions from untrusted user data has created a persistent and expanding attack surface. This paper presents a structured taxonomy of prompt injection attack vectors, including direct injection, indirect injection, multimodal attacks, tool and agent exploitation, hybrid chained techniques, and autonomous propagating threats. These vectors are mapped across five impact categories (data …

Tracing The Milky Way’S Evolution Through Its Star-Planet Systems, Rayna Rampalli

Dartmouth College Ph.D Dissertations

From individual planetary systems to the Milky Way's structure, stars are the linchpin connecting astrophysical scales. Through three complementary projects, my thesis leverages these connections and large stellar surveys to offer insight into the Galaxy's dynamical and chemical history and its role in shaping planet formation and evolution. (I) I developed Protify, an automated pipeline to measure stellar rotation periods in TESS light curves, enabling rotation-based ages for thousands of stars. Applying it to overdensities of stars in eccentric Galactic orbits, thought to be post-resonant signatures of spiral arm passages, revealed unexpectedly young rotators in dynamically old populations. Because such …

A Computer Vision Approach To Analyzing Taxane Effects On Prostate Cancer Cells, Diana Elizabeth Dancea

Electronic Theses and Dissertations

Actin is a family of proteins that help create the structure of the cytoskeleton, which gives shape to the cell. In many chemotherapy treatments, researchers target actin because it controls the cell division process. Therefore, if they are able to understand the actin fibers, that may help in formulating methods to stop or slow down cancer cells from reproducing. Another important protein is PAK6, which regulates actin. In our research, a collaborative effort with Prof. Michael Lu’s lab at Florida Atlantic University, we use machine learning techniques to analyze cells which had their PAK6 protein knocked out, and compare them …

A Backend Database Architecture For Persistent Epilepsy Classification Records, Attiksh A. Panda, Deep Desai, Artem Zabarov, Katrina D. Prantzalos, Satya S. Sahoo, Shuai Xu

Student Scholarship

Epilepsy affects over five million people globally each year, yet consistent clinical diagnosis remains a persistent challenge due to the lack of standardized classification workflows across medical institutions. The Four-Dimensional Epilepsy Classification (4D-EC) framework, developed by Lüders et al., provides a comprehensive structure for characterizing paroxysmal events across four dimensions: seizure semiology, epileptogenic zone, etiology, and comorbidities. Despite its clinical and educational value, no dedicated informatics platform existed to support its routine use until recently, limiting widespread adoption among clinicians and trainees. This project addresses that gap by implementing a full-stack web application that operationalizes the 4D-EC framework for clinical …

Quantum Simulation And Nanoscale Sensing Of Many-Body Phenomena With Solid-State Spin Defects, Guanghui He

Arts & Sciences Graduate Student Theses and Dissertations

Emergent phenomena in interacting quantum systems arise from collective behavior that cannot be reduced to single-particle physics. Understanding these phenomena requires platforms capable of both synthesizing many-body states under controlled conditions and probing them at the microscopic scale where correlations originate. Solid-state spin defects, including nitrogen-vacancy (NV) centers in diamond and negatively charged boron vacancy centers in hexagonal boron nitride (hBN), offer precisely this dual capability. In the first part of this dissertation, a strongly interacting NV ensemble is subjected to periodic and quasi-periodic drives to access a long-lived prethermal regime and realize a discrete time quasicrystal (DTQC). In the …

Re: Comment Letter For The Silver Bow Creek/Butte Area Npl Site Butte Priority Soils Operable Unit, 60% Remedial Design Documents For The Blacktail Creek Area Groundwater Hydraulic Control System (Dated March 2, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 96 – Washoe Dump Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Butte Priority Soils Operable Unit Unreclaimed Sites: Ur-03 Construction Completion Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Butte Priority Soils Operable Unit Unreclaimed Sites: Ur-03 Construction Completion Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

The Texture Of A Threat: Adversarial Training, Cnns, And Obfuscated Malware Detection, Kaelyn Haynie

Senior Honors Theses

Accurately detecting malicious programs is an expanding field of research for machine learning (ML), with a novel approach incorporating a bytecode-to-image pipeline that produces images representative of software. These images are provided to convolutional neural networks (CNNs) to be examined for malicious pattern indicators. However, CNNs struggle to generalize these patterns effectively while still being robust against adversarial data, an issue which this research addresses with adversarial training. In this paper, three unique CNN architectures (a DBFS-MC-inspired baseline, MIRACLE, and PSP-CNN) are trained for binary classification with 15,000 benign and malicious software samples encoded into images for Android, Windows, and …

Leveraging Convolutional Neural Networks For Through-The-Wall Radar Imaging: Challenges, Impacts, And Future Directions, Tumaini Edgar, Abdulla F. Ally, Abdi T. Abdalla

Tanzania Journal of Engineering and Technology (TJET)

Through-the-wall radar imaging (TWRI) is an essential technology for military and rescue applications; however, its performance in detecting and visualizing high-quality images of targets behind walls is significantly degraded by multipath reflections and signal attenuation. This paper reviews the current state of TWRI and its challenges, and explores the transformative potential of deep learning, particularly convolutional neural networks (CNNs), in addressing these challenges. Peer-reviewed articles published from 2018 to 2024 were analysed to examine CNN applications in addressing TWRI challenges. The analysis reveals that using CNNs, TWRI systems can be more effective by filtering wall distortions, reducing noise, lowering computational …

Bremsstrahlung Photons Emissions Measured At Different Rf Power In 28 Ghz Ecr Ion Source, Mwingereza John Kumwenda

Tanzania Journal of Engineering and Technology (TJET)

High-performance electron cyclotron resonance ion sources (ECRISs) generate large amounts of bremsstrahlung photons that affect the cryogenic systems due to the extra heat load that is produced. Thus, this study investigates the bremsstrahlung photons energy spectra at various RF powers, presenting some insight about the trends of the electron heating process inside the plasma. Bremsstrahlung photons from a 28 GHz ECRIS were measured at Busan center of Korean Basic Science Institute (KBSI). The gamma-ray detection system consists of three round-type NaI(Tl) scintillation detectors placed 620 mm radially from the beam axis at the extraction side of the ECRIS, and a …

Normal Matrices, Fuzhen Zhang

Mathematics Colloquium Series

Normal matrices form a central class in matrix analysis, including Hermitian, skew-Hermitian, and unitary, positive semidefinite, permutation matrices and so on. This presentation surveys fundamental properties of normal matrices, including spectral characterization, unitary diagonalization, and trace (in)equality through majorization. It highlights equivalent conditions for normality, with discussions extending to matrix exponentials and polynomials. Examples and counterexamples are provided to clarify certain subtle points about matrix normality. The talk is based on a recent paper published in JMC (joint work with Y.-J. Hu)

Are Certain Mobile Phones Overpriced?, Camron Pickard, Jennifer Schon

Celebration of Research

In this project, I investigated the possibility of projecting phone prices based on people’s opinions of their performance. I predicted that the more expensive phones would have higher rating predictions but have lower predicted prices.

Loan Risk Classification Model, Giulio Palombo

Celebration of Research

I created a model that classifies the customers as good or bad for possible loaners. The model is XGBoost Classification model. I used as target variable the variable “default”. The target variable indicates whether the customer has previously defaulted on a loan or not. The dataset provides a representation of customer behavior and financial status. On top of that, the dataset contains detailed information about banking transactions.

Emergent Dynamics In Multiplex Social Networks: Agent-Based Modeling Of Information Diffusion For Misinformation Control, Harshvardhan Prabhakar Ghongade, Anjali Ashokrao Bhadre, Shivani Agarwal, Harjitkumar Uttamrao Pawar, Harshal Subhash Rane

Northeast Journal of Complex Systems (NEJCS)

Information misrepresentation is widespread in multi-layered social networks which provide multiple avenues to communicate information. As such, it presents significant opportunities for both information integrity and public discourse to be undermined by disinformation. This paper outlines a new agent-based model, developed to capture emergent dynamics of multi-layered social networks and to help identify technical means to mitigate information misrepresentation in complex systems. A key component of this research includes a novel Multi-Layer Information Diffusion Model (MLIDM), integrating both cross-layer communication among agents, as well as heterogeneous agent behaviors and adaptive intervention strategies. Our methods employ a three-stage process to model …