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Interseismic Creep Along The Enriquillo–Plantain Garden Fault, Haiti, Estimated From Insar, Rishabh Dutta, Jeremy L. Maurer, Yi Chieh Lee

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The Enriquillo–Plantain Garden fault zone (EPGFZ) is a major left-lateral strike-slip fault in southern Haiti hosting several recent destructive earthquakes, including the 2021 MW 7.1 Nippes event with primary thrust-slip. To investigate how strain is accommodated in the vicinity of the 2021 event, we analyzed Sentinel-1 interferometric synthetic aperture radar (InSAR) data from 2017 to 2021 using a PS + DS (persistent + distributed scatterers) InSAR time-series approach to overcome decorrelation in this highly vegetated region. We reveal interseismic creep along the EPGF and adjacent Grand'Anse–Sud border faults, with pure strike-slip mechanism and rates up to 9 mm/yr. We suggest …

Cardiovascular Disease Subtypes And Alzheimer's Disease: Phenotypic And Genetic Associations In The Uk Biobank And All Of Us Research Program, Aili Toyli, Chen Zhao, Kuan Jui Su, Hui Shen, Hong Wen Deng, Qing Hui Chen, Qiuying Sha, Weihua Zhou

Michigan Tech Publications

BACKGROUND: Cardiovascular disease (CVD) and Alzheimer's disease (AD) are major public health concerns that share overlapping risk factors and potential mechanistic pathways. Although vascular contributions to cognitive decline are well documented, the specific relationships between AD and different CVD subtypes remain poorly understood. METHODS: In this cross-sectional study, we examined associations between AD and 11 CVD subtypes using logistic regression models in 2 large biobanks: the UK Biobank (n=502 133) and the All of Us Research Program (n=287 011). Models were adjusted for demographic, lifestyle, and clinical covariates. We also explored genetic overlap between AD and CVD traits through proximity-based …

Trophic Transfer Of Fluorescent Polyethylene Microplastics In A Simplified Artemia–Oreochromis Aquatic Food Chain, Dativa J. Shilla

Tanzania Journal of Science

Microplastics (MPs) are pervasive contaminants in aquatic ecosystems, yet experimental evidence of their trophic transfer within tropical African food webs remains scarce. This study provides experimental evidence of indirect trophic transfer of microplastics from Artemia salina to Oreochromis urolepis, a cichlid species of ecological and economic importance in African inland and coastal waters. A simplified two-level food chain was established by exposing A. salina nauplii to fluorescent polyethylene microplastics (10–20 µm; 1, 10, and 100 mg L⁻¹) and subsequently feeding them to juvenile O. urolepis under controlled laboratory conditions. These concentrations were selected to represent a range of exposure levels …

Optimization Of Bio-Briquettes Production From Cassava Stems Co-Blended With Sisal Bole Bagasse Using Response Surface Methodology, Agnes Nshoma Msobi, Neema O. Msuya, Kando Khalifa Janga

Tanzania Journal of Science

This research aimed at producing bio-briquettes from cassava stems and sisal bole bagasse as an alternative source of cooking energy. A Response Surface Methodology (RSM) with Face - Centered Central Composite Design (FCCCD) featured a multi-objective optimization of the effect of the production parameters, focusing on maximizing char yield and Higher Heating Value (HHV) of the produced briquette while minimizing carbonization temperature and residence time. The findings showed that bio-briquettes produced at the lowest temperature (250 ℃) and residence time (30 min) and the blending ratio of 75% by 25% had the highest char yield of 76.92% and HHV of …

A System For The Prediction Of Election Results Using Vader And Hybridized Machine Learning Model, Abraham E. Evwiekpaefe, Khadijah Kabir, Georgina N. Obunadike

Tanzania Journal of Science

Integrating different classifiers along with sentiment lexicons like Vader, can enhance the performance of sentiment analysis systems. However, such a hybrid model remains underexplored, particularly in the context of regional elections in developing countries like Nigeria. The aim of this research is to develop a hybrid model that combines three machine learning classifiers and Vader lexicon to possibly achieve a higher accuracy. A case study of the 2023 governorship election in Kogi, Bayelsa and Imo State, Nigeria was examined. Twitter API library was utilized to extracted public and personal tweets using hashtags and keywords related to the target data from …

Extraction Of High-Quality Cashew Nutshell Liquid Using Carbon Dioxide-Expanded Hexane, Frank N. Jacob, Neema Msuya, Joseph Y.N Philip, Kando Khalifa Janga

Tanzania Journal of Science

Cashew nutshell liquid (CNSL) is a by–product from cashew processing industries containing four naturally occurring phenolic compounds. This study investigated an extraction approach using CO2–expanded hexane. The central composite design (CCD) was employed in experimental design to investigate the effects and interaction of CO 2 mole fractions and extraction temperature on the CNSL yield and quality (Colour) from Steamed CNSL. The dissolution power of the CO2–expanded hexane was assessed by determining the solubility of CNSL during the initial stages of extraction at different extraction conditions. Findings indicated that higher CO2 mole fractions reduced CNSL solubility, while higher temperatures enhanced it. …

Multi-Frequency Associative Memory For Continual Graph Learning Through Nested Optimization, Shuvam Kundu

Master’s Dissertations

Graph Neural Networks struggle to learn new tasks without forgetting old ones a problem known as catastrophic forgetting. In graph domains, this is compounded by structural shift, where newly added edges corrupt the learned representations of historical nodes even when model weights remain unchanged. We present CAM-Titans, a continual graph learning framework built around a two-buffer associative memory to address both parametric and structural forgetting. Our architecture operates across three timescales of adaptation: a slow base memory updated via ordinary gradient descent, an intermediate task buffer re-encoded after every task using the delta-rule, and a transient in-context state for rapid …

A Study Of Prompt Tuning On Small Language Models(Slms): A Controlled Benchmark And A Lightweight Instance-Aware Method, Narkadamilli Sahith

Master’s Dissertations

Parameter-efficient fine-tuning (PEFT) adapts a frozen pre-trained language model by training only a small number of additional parameters. Among PEFT approaches, prompt tuning prepends trainable continuous vectors (soft prompts) to the input. A recurring finding in the literature is that prompt tuning is strongly scale dependent: it rivals full fine-tuning on very large models but lags on smaller ones. This dissertation studies prompt tuning specifically in the small-language-model (SLM) regime. We (i) re-implement a representative set of prompt-tuning methods—Prompt Tuning, P-Tuning v2, LoPT, DPT, DePT, ACCEPT, Residual Prompt Tuning, and PARA—within a single controlled harness, enabling a fair head-to-head comparison …

Reproducing And Analyzing The “Lost In The Middle” And “The Power Of Noise” Phenomenon In Retrieval-Augmented Generation, Kousik Samanta

Master’s Dissertations

Retrieval-Augmented Generation has become the way to improve Large Language Models. They help with problems like knowledge and hallucinations. Recent studies show that these models still have limitations. One big problem is the “Lost in the Middle” phenomenon. Models can’t access information in the middle of contexts properly. Another counterintuitive observation is the “Power of Noise” paradigm, which suggests adding unrelated documents can actually make the generation better. We know these happen in extractive QA tasks, but we don’t know if they happen in tasks that need complex reasoning. This dissertation looks into how position and noise affect Long-Form Question …

Learning To See Lesions, Not Skin Tone: Counterfactual Multimodal Learning For Fair, Trustworthy, And Text-Free Dermatology Ai, Shivam Jangid

Master’s Dissertations

Recent advances in deep learning have significantly improved the performance of automated skin lesion classification systems, enabling accurate detection of various dermatological conditions from medical images. Despite these achievements, concerns regarding fairness and generalization remain a major challenge for the deployment of such systems in real-world clinical settings. A key factor contributing to these challenges is the presence of bias in training datasets, particularly with respect to skin-tone representation. Most publicly available skin lesion datasets contain a disproportionate number of samples from individuals with lighter skin tones. As a result, deep learning models trained on these datasets often learn representations …

Adaptive Spectral Trust Gate For Physics- Constrained Operator Learning, Soham Chakraborty

Master’s Dissertations

Physics-informed machine learning improves the plausibility, data-efficiency and generalization of surrogate models by injecting prior physical knowledge into the learning process. The current approaches can be broadly divided into two main categories: soft constraints, which add a physics residual to the training loss but guarantee nothing at inference time, and hard constraints, which project the model output onto the constraint set exactly but apply the projection uniformly to every part of the signal — including parts that are dominated by noise, discretization error, or model mismatch, where the idealized physics is not actually trustworthy. This dissertation proposes the Adaptive Spectral …

Deep Reinforcement Learning With Directed Asymmetry And Kolmogorov-Arnold Networks For Dismantling Interdependent Multiplex Networks, Soumyajit Dev

Master’s Dissertations

Identifying the minimum-cost node-removal sequence that fragments a complex network - the network dismantling problem is NP-hard and central to infrastructure resilience. In interdependent multiplex networks, this difficulty is compounded by cascading cross-layer failures. While deep reinforcement learning (DRL) agents utilizing graph neural network (GNN) encoders achieve near-optimal dismantling, current state-of-the-art architectures suffer from two critical limitations. Topologically, existing agents strictly assume undirected edges, rendering them inapplicable to directed systems - such as supply chains or gene regulatory cascades - where failure propagation is fundamentally asymmetric. To resolve this, we propose Disassembling Directed Interdependent Networks (DDIN). DDIN introduces an asymmetric …

Direct Minimization Of Hartree-Fock-Roothaan Energy Functionals Using Derivative-Free Optimization Algorithms: A Case Study On The Use Of Noninteger Slater-Type Orbitals, Ali̇ Bağci

Turkish Journal of Physics

This study presents an evaluation of derivative-free optimization algorithms for the direct minimization of Hartree−Fock−Roothaan energy functionals involving nonlinear orbital parameters and noninteger-order quantum numbers. The analysis focuses on atomic calculations employing noninteger Slater-type orbitals. Analytic derivatives of the energy functional are not readily available for these orbitals. Four methods are investigated under identical numerical conditions: Powell’s conjugate−direction method, the Nelder−Mead simplex algorithm, coordinate-based pattern search, and a model-based algorithm utilizing radial basis functions for surrogate-model construction. Performance analysis is first carried out using the Powell singular function, a well-established test case exhibiting challenging properties, including Hessian singularity at the …

Antioxidant Potential Of A Non-Heme Iron Complex: Mitigating H2O2-Induced Cellular Damage, Magy A. Mekhail, David M. Freire, Cameron Bowers, Grant Elam, Nora Del Bosque, Hannah K. Pyle, Sarah K. Dunn, Spencer Lanyon, Timothy J. Hubin, Giridhar Akkaraju, Kayla N. Green

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Iron complexes with antioxidant activity have garnered significant interest for both general and medical applications, yet few studies have yielded functional nonheme iron-based mimics for H₂O₂ mitigation in aqueous environments. Here, we investigate water-soluble nonheme iron complexes derived from 12-membered pyridinophanes (^CF₃PyN₃, PyN₃, ^NMe₂PyN₃, and Py₂N₂) to evaluate the impact of ligand scaffolds on H₂O₂ decomposition activity both in vitro and in a cellular model. Speciation and kinetic analyses reveal that both electronic and geometric modulation of the macrocyclic …

Adding 3,4-Methylenedioxy-Α-Cyclohexylaminopropiophenone To A Standard Operating Procedure (Sop) For Identifying Synthetic Cathinones Using Gas Chromatography-Mass Spectrometry, Napassawon Timpratoom

ETDs from 2020-2029

Synthetic cathinones were identified as new psychoactive substances (NPS) in the early warning advisory system by the United Nations Office on Drugs and Crime (UNODC). Synthetic cathinones have been commonly referred to as bath salts, which offered “legal highs” because they were not explicitly scheduled. These compounds were detected dur-ing the screening process in casework and required internal validation for confirmation. 3,4-methylenedioxy-α-cyclohexylaminopropiophenone was the target analyte for this study. It was alternatively named N-cyclohexyl methylone and “cyputylone." The aim of the study was to validate 3,4-methylenedioxy-α-cyclohexylaminopropiophenone into a Standard Operating Procedure (SOP) for identifying synthetic cathinones using gas chromatography/mass spectrometry …

Load Profile Analysis And Forecasting For Rural Mini Grids In Uganda, Prossy Mutesi, Santos L. Kihwele, Emmanuel S. Matee

Tanzania Journal of Science

Accurate load forecasting is essential for the reliable and cost-effective operation of rural mini grids, where constrained generation capacity and high penetration of renewable energy resources require well-informed operational decisions. This study examines electricity demand characteristics and forecasting performance for the Buzaami and Ssenyondo mini grids in Uganda, with particular focus on diurnal load profiles, peak demand behavior, and seasonal variability. 2022 operational data show extended peak demand from early morning to late evening, driven by socio-economic activities that strain resource scheduling and reliability management. To address these challenges, the study evaluates and compares Long Short-Term Memory (LSTM) networks, fuzzy …

New Studies In Lattice-Based Cryptography, Quantum Algorithms, And Privacy-Preserving Computation, Hansraj Jangir

Electronic Theses and Dissertations

Classical public-key cryptographic schemes primarily rely on the presumed hardness of the integer factorization and discrete logarithm problems. However, Shor’s algorithm demonstrates that both problems can be solved efficiently on a sufficiently powerful quantum computer. This breakthrough motivated the search for quantum-resistant hard assumptions. The assumptions based on lattices are one of the primary candidates in post-quantum cryptography due to their strong theoretical foundations and well-established hardness against both classical and quantum attacks. In this thesis, we explore several directions of lattice based cryptology and quantum algorithms.

On the construction side, we propose two compact encryption schemes based on the …

Pinnlab: An Interactive Dashboard For Teaching Data-Driven Parameter Estimation In Differential Equations Using Physics-Informed Neural Networks, Mohan J. Parthasarathy, Padmanabhan Seshaiyer

CODEE Journal

Undergraduate instruction in ordinary differential equations (ODEs) is typically organized around the forward problem: finding solution trajectories when the governing equation and its parameters are known. In scientific practice, however, inverse problems are often more relevant, requiring unknown parameters to be inferred from noisy observations while assessing whether a proposed model is consistent with the data. We introduce PINNLab, an open-source MATLAB dashboard designed to help undergraduate students explore inverse modeling through physics-informed neural networks (PINNs). PINNLab presents PINNs as a complementary data-driven framework that connects differential equations, optimization, empirical data, and scientific machine learning. The instructional sequence is organized …

Robust Real-Time Uav Target Tracking With Onboard Vision-Based Yaw Control, Rylan Malarchick, Jose Castelblanco, Enrique Amaya, Carmen Dimario, Graysen Brinkman, Chirag Kumar, Kiwon Yoon, Sajid Berhane

Beyond: Undergraduate Research Journal

Autonomous tracking of agile unmanned aerial vehicles (UAVs) presents significant challenges for real-time perception and control systems. This work presents AIRHOUND (Autonomous Intelligent Rotorcraft for Hostile Object Unified Navigation and Detection), a UAV platform implementing vision-based yaw tracking through a modular ROS2 software architecture. The system employs YOLOv8 object detection optimized with NVIDIA TensorRT for embedded deployment on an NVIDIA Jetson Orin companion computer. Detected targets are processed through a geometric tracking module that converts pixel coordinates to angular yaw errors using pinhole camera intrinsics, with a proportional controller generating rate-limited yaw commands. These commands are streamed to a PX4 …

Impact On Energy Budgets In Grassland Production And Conservation Of Possible Production Of Energy From Biomass Crops, R J. Wilkins

IGC Proceedings (1977-2023)

There is commonly a conflict between output/unit of area of land and output/unit of support-energy (SE) input. The possibil­ity of using a proportion of the total land area for biomass energy production suggests an approach for calculating grassland out­put/ha unconfounded with differences in SE input. Output can be calculated for an area of land that is devoted to grassland and biomass energy crops in proportions that result in a net demand for SE of zero. Outputs of utilized metabolizable energy (UME) are related to inputs of SE for (1) grazed grass with high application of nitrogen (N) fertilizer and (2) …

Efficiency Of Dairying Under Contrasting Feeding And Management Systems In North America, Israel, Europe, And New Zealand, J.D. J. Scott

IGC Proceedings (1977-2023)

Four different systems of feeding and managing dairy cattle are seen in major milk-producing countries. These are (1) feeding purchased roughages and concentrates to zero-grazed, intensively penned cows; (2) home growing of roughages and most con­centrates for zero-grazed animals; (3) feeding concentrates with conserved pasture and other roughages in winter and reduced concentrates to grazed cattle in spring-summer; and (4) feeding cattle on grazed pasture and conserved pasture throughout the year. The following data on the four systems were obtained from examples in southern California, Wisconsin, England/Wales, and New Zealand. Average fat-corrected milk (FCM)/cow is approximately 7,140, 5,300, 4,670, and …

Potential Contribution Of White Clover To The Economics And Support-Energy Inputs Of Grass-Based Beef-Production Systems, T A. Stewart, R E. Haycock, A S. Laidlaw

IGC Proceedings (1977-2023)

Biological output, gross margins, and efficiency of support-energy usage in an 18-month beef-production system on grass-white clover swards receiving either 50 kg N/ha stocked at 3.3 head/ha (low N) or 300 kg N/ha stocked 4.5 head/ha (high N) were compared. To date, two production cycles (1977-1979 and 1978-1980) at two sites have been completed. Mean live-weight and carcass gains/ha were, respectively, 17.5% and 14% higher from the high-N than from the low-N system. Gross margin/head was higher from the high-N system in the first production cycle but not in the second. In the low-N system as com· pared with the …

An Evaluation Of The Black Walnut- Tall Fescue Pasture-Management System, H E. Garrett, W B. Kurtz

IGC Proceedings (1977-2023)

The economic and biological feasibility. of a black walnut-livestock-grazing multicropping-management regime bas been evaluated for comparison with a similar livestock-management regime conducted in the open. Pure tall fescue plots were established under open and black walnut-shade conditions. Forage yields on a dry-weight basis were estimated for a 3-year period. A concurrent grazing trial was co􀀌ducted on similar sites using 1.2-ha plots. Black walnut seedlings were planted within the plots on a 3 x 12-m spacing and protected from grazing animals by electric fencing. The economic analyses of the alternate grazing systems were based on their respective present net worth and …

Economics Of Renovating Mountain Hay Meadows, J J. Jacobs

IGC Proceedings (1977-2023)

There are approximately 0.5 million hectares (ha) of irrigated native grass hay in the mountain and intermountain regions of California, Oregon, Idaho, Utah, Nevada, Montana, Wyoming, and Colorado. Often these lands are not producing at their full physical or economic potential. The objectives of this study were to identify alternative improvement procedures to increase hay production and to determine the economic feasibility of those alternatives. The principal means of identifying alternative mountain hay-meadow improvement practices and their costs was personal in­terviews with ranchers. The ranchers interviewed were owners and/or operators of mountain ranches in Wyoming who were us­ing or had …

Pasture Demonstration Program For Beef: Economic Considerations, P R. Hasbargen, R H. Craven, N P. Martin

IGC Proceedings (1977-2023)

This study made an economic evaluation of several alternative pasture improvement programs on beef farms in northern Minnesota. Three questions were addressed relative to several pasture improvement systems. These were (1) Will it pay? (2) Is there a cheaper way? and (3) Is there a more profitable system for a particular farm resource situation? Partial budgeting and computerized linear programming techniques were used to analyze pasture cost and return data obtained from several ranches in northern Minnesota. Study results show that rented pastures, when available, provided the cheapest source of additional summer feed, and that legume pastures provide cheaper sources …

Pennsylvania's Alfalfa Growers Program: Four Years Of Success, J E. Baylor, L E. Lanyon, W K. Waters

IGC Proceedings (1977-2023)

Alfalfa (Medicago sativa L.) is the most important perennial forage legume grown in Pennsylvania. However, yields currently reported by farmers are considerably below what might be expected when all production inputs are utilized. Therefore, a pro­gram was developed (1) to measure how much alfalfa hay, protein, and energy can be pro􀀗uced on 1 ha of Pennsylvania land under nonirrigated conditions, (2) to determine the mineral content and uptake by high-yielding alfalfa crops, and (3) to obtain more realistic on-farm estimates of alfalfa production costs. To achieve the program goals, hay production for each harvest from 2.02-ha farm fields was …

Estimation Of Digestibility Of Legume Forages By Means Of Morphological Parameters, W Kuhbauch

IGC Proceedings (1977-2023)

Forage quality is normally evaluated by time-consuming and costly laboratory analyses. It appears promising to use mor­phological parameters to evaluate forage quality in alfalfa and red clover. During progressive growth of white clover, red clover, and alfalfa, the leaf and stem portion was separated to determine the fiber fraction according to the Van Soest method and to

estimate digestibility by the procedure of Tilley and Terry. Stem : leaf ratio and stand height as a measure of stem length were used as morphological parameters. Leaves of the three legumes vary only slightly in concentration of cell-wall material and in digestibility …

Income, Costs, And Profits Associated With Feeding Selected Forages To Dairy Cows, D D. Dornfeld, D A. Rohweder, W T. Howard

IGC Proceedings (1977-2023)

Over the last i0 years, dairy-farm enterprises have g:ro-wn in size, with an apparent increase in use of improved scientific feeding and management techniques. There in growing emphasis on automated feeding and milking and on management stcategies in an attempt to reduce labor needs and allow more cows/worker. The average herd size in the sample population was 76.8 cows. There was difficulty finding herds over 100 and under 40 head. It appears that the trend toward increasing growth will continue, as much as sufficient capital, management ability, and debt service capacity eJi:ist to permit the growth to occur. Forage management …

Economic Analysis Of The Impact Of Management Decisions On Production And Use Of Silage For A Dairy Enterprise, A J. Corrall, H D. St. C Neal, I M. Wilkinson

IGC Proceedings (1977-2023)

The aim of this work was to examine the influence of variations in grass management and methods of ensiling on the economics of milk production for autumn-calving cows. A simulation model was developed to combine knowledge of plant and animal responses and their interactions in order to calculate the effects of management options on economic balances. Input data were compiled for herbage production from cut­ting strategies that gave herbage at four digestibilities, at two levels of applied nitrogen, and in three climates. Experimental evidence was also collated to construct matrices of loss of dry matter and changes in digestibility and …

Role And Effectiveness Of U.S. Universities In Training Professionals For Work In International Agriculture, D F. Fienup

IGC Proceedings (1977-2023)

Problems of hunger, malnutrition, and world food security became a major world concern in the 1970s. Two U.S. presiden­tial reports have emphasized the seriousness of the situation and the need to expand food production and distribution, par­ticularly in the less-developed countries (LDCs) where hunger is most severe. The LDCs need to strengthen agricultural teaching, research, and extension in order to develop and disseminate the ap­propriate technology farmers need to increase food production. The most limiting factor is often the lack of trained scientists to provide local leadership and expertise. Here U.S. and other developed-country universities are needed to train LDC …