Digital Commons Network^™

Effect Of Protective Mutation On Structure And Dynamics Of Apoe: A Molecular Dynamics Simulation Study, Newton A. Ihoeghian, Usman L. Abass, Ibrahim A. Imam, Qing Shao

Chemical and Materials Engineering Faculty Publications

Apolipoprotein E (APOE) plays a significant role in determining the risk of Alzheimer’s disease (AD). Three mutations—APOE3–R136S, APOE3–V236E, and APOE4–R251G—have been reported to reduce the risk of AD. Unveiling the molecular mechanism behind this reduction could lay a foundation for developing therapeutics for AD. To shed light on this subject, we investigate the mutation-induced variation in structural and dynamic properties of APOE3–R136S, APOE3–V236E, and APOE4–R251G in explicit solvent using molecular dynamics simulations. The APOE2, APOE3, and APOE4 were used as the reference. The analysis unveiled that the three protective mutations may exert protection through different mechanisms. The R215G mutation makes …

Tiny Plastic, Big Trouble: How Polystyrene Nanoparticles Impact Dna-Damage Repair Deficient Cervical Cancer Cells, Jordan D. Berezowitz, Mira C. Fish, Lauren E. Mehanna, Breanna Knicely, Claire E. Rowlands, Eva M. Goellner, Brittany E. Givens

Chemical and Materials Engineering Faculty Publications

Microplastics are becoming increasingly abundant waste products; therefore, the risk of human exposure is also increasing. The cytotoxic consequences of microplastic exposure, particularly in cancer, have yet to be explored. We obtained commercially available polystyrene nanoparticles of uniform size (86.61 ± 6.41 nm) and confirmed the chemical composition and shape using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM), respectively. We evaluated colloidal stability over a range of concentrations from 1–1000 µg mL⁻¹ using hydrodynamic diameter and zeta potential, determining that higher concentrations exhibit greater colloidal stability compared to lower concentrations. Specifically, the zeta potential increased from …

A Simple Statistical Tool To Correct The Daily Temperature Effect On Dielectric Soil Matric Potential Sensor Readings, Sebastián Bravo Peña, Meindert Commelin, Ole O. Wendroth

Plant and Soil Sciences Faculty Publications

High-resolution time series recorded by soil water dielectric sensors are often affected by other processes. Dielectric soil matric potential sensors, such as the TEROS 21, exhibit temperature sensitivity, resulting in deviations of readings from the true value due to soil temperature fluctuations. However, methods for correcting this effect remain limited. The objective of this study was to create a straightforward, scale-based statistical approach to mitigate the influence of daily temperature oscillations on matric potential dielectric readings. The temperature sensitivity correction function (TSCF) identifies, quantifies, and smooths diurnal fluctuations caused by soil temperature dynamics. We provide a detailed description of the …

Current And Emerging Therapeutic Strategies For The Treatment Of Duchenne Muscular Dystrophy, Miguel A. Lopez Perez, Noah L. Weisleder

Molecular and Cellular Biochemistry Faculty Publications

Background/Objectives: Duchenne muscular dystrophy (DMD) is a fatal, progressive neuromuscular disorder caused by mutations in the dystrophin gene, leading to the absence of functional dystrophin protein. As the largest gene in the human genome, the DMD locus is highly susceptible to mutations, contributing to a prevalence of approximately 1 in 3800–6300 live male births worldwide. This review aims to provide a comprehensive and critical synthesis of current and emerging therapeutic strategies for DMD.

Methods: We conducted a narrative review of the literature, integrating findings from clinical trials, regulatory approvals, and preclinical studies. We categorized therapeutic approaches into mutation-agnostic and mutation-specific …

Federated Data Engineering And Learning For Edge Intelligence Systems, Afsaneh Mahanipour

Theses and Dissertations--Computer Science

The rapid proliferation of Internet of Things (IoT) devices and cyber–physical systems (CPS) in domains such as smart healthcare, intelligent transportation, and industrial automation has led to unprecedented volumes of heterogeneous data. While advances in deep learning and large-scale foundation models have enabled powerful data-driven decision making, their deployment in real-world distributed environments remains fundamentally constrained by limited computation, communication bandwidth, energy resources, and data privacy requirements. This dissertation addresses these challenges by developing novel federated learning frameworks and efficient federated data-processing pipelines that make large-scale artificial intelligence practical, scalable, and trustworthy in resource-constrained settings. This dissertation identifies data preprocessing …

Multi-Objective Optimization Of Energy Costs And Ev Battery Health In V2g Enabled Homes, Dzifa M. Hodey

Theses and Dissertations--Computer Science

Electric vehicles (EVs) and rooftop solar photovoltaic (PV) systems are increasingly being integrated into residential settings, creating new opportunities for vehicle-to-grid (V2G) and vehicle-to-home (V2H) operations. In these systems, the EV battery functions as a controllable energy storage unit that can charge from the grid or PV and discharge energy to supply household load or export to the grid for a profit. By intelligently scheduling this bidirectional power exchange, households can reduce electricity costs and enhance PV utilization. Realizing these benefits requires optimization strategies that balance cost reduction with EV battery health preservation. However, existing V2G/V2H studies largely emphasize cost …

Toward Efficient And Scalable Scientific Data Management Through Quality-Oriented Data Compression, Pu Jiao

Theses and Dissertations--Computer Science

Scientific simulations and instruments now produce data at rates that overwhelm the storage, memory, and network subsystems of modern high-performance computing (HPC) facilities. Error-bounded lossy compression reduces data movement costs while bounding reconstruction error, yet three barriers limit its adoption in mission-critical workflows: existing compressors cannot guarantee the accuracy of domain-specific quantities of interest (QoIs) derived from compressed data; compression-induced artifacts such as posterization, blocking, and interpolation banding erode user confidence in decompressed fields; and significant compressibility in the quantization index arrays of interpolation-based pipelines remains unexploited. This dissertation addresses all three barriers through four contributions, with the artifact barrier …

Advancing Task-Oriented Dialog Systems: Scalability, Generalization, And Evaluation, Adib Mosharrof

Theses and Dissertations--Computer Science

Task-oriented dialog (TOD) systems enable conversational interfaces for complex tasks like flight booking and restaurant reservations. However, deploying TOD systems at scale faces three critical barriers: scalability, generalization, and evaluation. Scalability is primarily restricted by the human-annotation bottleneck, as current systems depend on vast quantities of manually labeled data for every new domain, making deployment prohibitively expensive. Generalization remains a persistent challenge, as systems optimized for known domains often suffer significant performance degradation when encountering new, unseen ones. Existing evaluation metrics measure response quality and fluency, but fail to measure functional task success. As TOD systems are deployed across diverse …

Advancing Generative Methods For Multimodal Data Analysis, Rabeya Tus Sadia

Theses and Dissertations--Computer Science

The integration and modeling of high-dimensional, heterogeneous biological data remain central challenges in computational biology due to complex feature dependencies and pervasive missingness. This dissertation addresses these challenges by developing novel generative frameworks for multimodal data reconstruction, imputation, and interaction prediction. In generative modeling, we focus on capturing structural and causal dependencies in sparse biological systems. We first introduce CausalGeD, a causality-aware diffusion framework that leverages Granger-causal attention for biologically coherent spatial gene expression generation. Next, we propose CausalGenDiff, which combines VAE-guided latent representations with causal diffusion to enable robust reconstruction across spatial and single-cell modalities. We further present DepMicroDiff, …

Vision‑Based Online Quality Tracking In Wire Arc Additive Manufacturing Via Hybrid Unsupervised Deep Learning–Statistical Process Monitoring, Giulio Mattera, Yue Cao, Yuming Zhang, Luigi Nele

Electrical and Computer Engineering Faculty Publications

Vision-based monitoring of Wire Arc Additive Manufacturing (WAAM) using supervised deep learning represents the state of the art in anomaly detection, but such approaches require large labeled datasets that are costly to obtain and typically limited to laboratory conditions. To address these limitations, this work proposes a hybrid deep learning–statistical process monitoring (SPM) framework tailored to the stochastic nature of conventional arc welding processes such as GMAW-based additive manufacturing, where existing methods often overfit. The framework integrates a residual convolutional autoencoder (Res-CAE) with skip connections, which jointly analyzes video frames to generate refined latent-space features that are subsequently monitored using …

Animal Models Of Aortic Aneurysm And Dissection: A Comparative Guide For Mechanism, Therapeutic Testing, And Translational Readouts, Shayan Mohammadmoradi, Sidney W. Whiteheart

Saha Cardiovascular Research Center Faculty Publications

Aortic aneurysms and dissections are devastating vascular diseases with high mortality, yet no pharmacological therapy has proven effective in halting growth or preventing rupture. Surgical and endovascular repair remain the only treatment options for advanced disease. Animal models have been indispensable in defining mechanisms and testing candidate therapies, but the diversity of protocols, strain-dependent variability, and heterogeneous endpoints complicate interpretation and translation. This review provides an update focused on how to match models to specific research questions. We critically compare commonly used abdominal aortic aneurysm (AAA) models (angiotensin II ± hyperlipidemia, elastase, calcium chloride, β-aminopropionitrile BAPN hybrids, and mineralocorticoid agonist/fludrocortisone …

Feasibility Study Of A Screening Decision Tool For Allocating Adults Into Food Is Medicine Programs As An Effective Approach To Target Clinical And Dietary Outcomes Among Rural And Urban Adults, Alison Gustafson, Carolyn Lauckner, Joshua L. Bush, Emily Dimond, Carolina Morales Serrano, Christa Mayfield, Elizabeth T. Anderson Steeves

Dietetics and Human Nutrition Faculty Publications

Objective: Evaluate feasibility (primary), clinical, and cost outcomes (secondary) associated with the use of a screening decision tool for allocating rural and urban adults with hypertension into in a food is medicine (FIM) program.

Design: Participants were allocated to receive either medically tailored meals or grocery prescription (Rx), based on a user-centered designed screening decision tool. Medically tailored meals (MTM) provided 5 meals per week for 12 weeks. The grocery Rx program provided $100 each month for 3 months to purchase food consistent with guidelines for hypertension. Feasibility outcomes included engagement, dose, and program acceptability. Semi-structured interviews were completed with …

Effective Deep Learning Architectures For Structured Data Analysis And Generation, Md Atik Ahamed

Theses and Dissertations--Computer Science

The effective utilization of structured data is fundamental to modern machine learning, yet it presents distinct challenges in both predictive analysis and generative modeling. Traditional deep learning architectures, particularly Transformers, often suffer from quadratic computational complexity when processing long sequences. This dissertation addresses these limitations by introducing novel architectures based on State-Space Models (SSMs) and Diffusion Models. In the area of predictive analysis, we focus on overcoming the computational bottlenecks of attention mechanisms for tabular and time-series data. First, we introduce MambaTab, a selective state-space architecture designed for efficient tabular classification. By leveraging the linear complexity of SSMs, MambaTab significantly …

Different Destinations: Clarifying And Addressing Pipeline Problems For Women In Academic Archaeology, Scott R. Hutson, Jaycee Castro, Bruno Athie Teruel

Anthropology Faculty Publications

In STEM fields, women tend to leak out of the pipeline to the professoriate. In archaeology, however, robust databases and chronological control reveal that there is no leakage from earning a PhD to tenure-track positions. Nor is there a leak from assistant professor to associate professor. Nevertheless, men get hired as faculty in PhD programs more often than women. This is important because PhD programs are research-intensive and train future leaders. Furthermore, women PhD students have women as advisers more than often men and report advantages to this arrangement. Yet with fewer women faculty in PhD programs, women mentors are …

Chirp Imaging In Extant Lakes And Reservoirs, Kevin L. Woller, Edward W. Woolery, Eva C. Lyon, Michael M. Mcglue

Earth and Environmental Sciences Faculty Publications

Compressed high-intensity radiated pulse (CHIRP) acoustic reflection data acquired in lakes and other shallow water bodies can provide detailed imaging that is valuable for environmental and engineering geology applications well below the sub-bottom floors. However, it is often unclear to non-specialists which acquisition settings should be considered to achieve optimal imaging quality when beginning a new survey, particularly in an unfamiliar environment. We review fundamental concepts for optimizing signal design using coincident CHIRP lines from two extant glacial lakes in the eastern Sierra Nevada of California: Convict Lake and June Lake. As part of the optimization process, seismic data were …

A Comparative Analysis Of Governance And Financial Frameworks In Public Transit Systems: A Case Study Of Lextran And Peer Transit Agencies, Kelin E. Beattie

MPA/MPP/MPFM Capstone Projects

Public transportation serves as a vital community "lifeline," providing essential mobility for the 45% of Americans without private vehicle access and generating a 5-to-1 economic return on investment. This research investigates a critical fiscal paradox within Lextran, the transit authority for Lexington, Kentucky: despite achieving a cost per passenger trip 22% lower than the national peer average, the agency faces a $25.95 million unfunded capital gap over the current five-year planning horizon. Utilizing a comparative case study methodology, this paper evaluates the "rules of the game"—the hybrid governance and fiscal frameworks—that influence long-term financial sustainability.

The study benchmarks Lextran against …

Sustainable Safety Planning On Two-Lane Highways: A Random Forest Approach For Crash Prediction And Resource Allocation, Fahmida Rahman, Cidambi Srinivasan, Xu Zhang, Mei Chen

Civil Engineering Faculty Publications

During the safety planning stage, accurate crash prediction tools are critical for prioritizing countermeasures and allocating resources effectively. Traditional statistical approaches, while long applied in this field, often depend on distributional assumptions that may introduce bias and limit model accuracy. To address these issues, studies have started exploring Machine Learning (ML)-based techniques for crash prediction, particularly for higher functional class roads. However, the application of ML models on two-lane highways remains relatively limited. This study aims to develop an approach to integrate traffic, geometric, and critically, speed-based factors in crash prediction using Random Forest (RF) and SHapley Additive exPlanations (SHAP) …

Effects Of Metal-Modified Catalysts On The Desorption Performance Of Mixed Amine Solutions And Machine Learning Prediction, Xunxuan Heng, Zhenzhen Zhang, Longhua Zhu, Li Yang, Shugang Xie, Zeyu Wang, Dongtai Han, Fang Liu, Kunlei Liu

Mechanical Engineering Faculty Publications

The high energy penalty associated with solvent regeneration is still a major bottleneck in amine-based CO₂ capture. In this work, the effects of five solid acid catalysts on the desorption performance of a mixed-amine solvent were compared, and the HY catalyst with superior desorption behavior was selected and further modified with four transition metals (Co, Mn, Gr and Ce) to enhance its catalytic activity. The findings indicate that the CO₂ desorption capacity and maximum desorption rate of the Co-modified HY catalyst reach 48.96 mmol and 0.02211 mmol/s, corresponding to increases of 36.80% and 35.39% relative to the blank …

Anuran Occupancy Of Created Wetlands Within Reforested Legacy Surface Mines In Kentucky And West Virginia, Jillian C. Newman, Steve Price, Jacquelyn C. Guzy, Joshua Castle, John J. Cox, Jeffery L. Larkin, Christopher D. Barton

Forestry and Natural Resources Faculty Publications

Restoration of habitat is an important component of wildlife management. Surface coal mining has altered forest cover in the Central Appalachians, and most reclamation activities on previously mined lands result in non-native grasslands or shrub lands. The Forestry Reclamation Approach (FRA), which emphasizes non-native vegetation removal, soil decompaction, planting of native trees and shrubs, and, in some cases, wetland creation represents an alternative to grassland-based reclamation that may promote forest-associated wildlife on legacy surface mines. We used automated recording units to evaluate the response of anurans to created wetlands and the FRA in Kentucky and West Virginia, USA. We used …

Sharp Dual-Regime Thermal Transition Driven By Bead Morphology In Metal Fused Filament Fabrication, Martin Gamesu, Nelson K. Akafuah

Mechanical Engineering Faculty Publications

This work develops a GPU-accelerated, bead-resolved digital twin for FFF that reconstructs super-elliptic filament geometries from G-code and simulates transient heat transfer via voxel-level activation synchronised to deposition order. Applied to a parametric study of two metal–polymer composites (Cu–PLA and IN718–PLA) across five super-ellipse exponents (n = 2.0, 2.7, 2.8, 2.9, 3.0), the framework reveals a sharp thermal regime transition: a 43% increase in interlayer contact width (n = 2.0 → 2.7) and 53% (n = 2.0 → 2.9) produce negligible thermal change (|Cohen’s d| < 0.02 for IN718-PLA and < 0.2 for Cu-PLA), while n = 3.0 triggers +150–178% increases in bonding windows, −55 to −60% reductions in cooling rate, and a 27–45-fold increase in thermal reactivation. The transition amplifies across temperature thresholds (2× at 170 °C, 15.8× at the glass transition), reverses the deposition-order thermal gradient (r = −0.83 to +0.64 for IN718-PLA and −0.55 to +0.81 for Cu-PLA), and causes surrogate model failure (cross-regime R² = −4.6). These findings establish bead morphology as a sharp morphology-driven threshold requiring regime-aware, material-specific digital twin. At the transition, weld-strength increases while cooling-rate decreases, indicating improved bonding uniformity and reduced residual-stress heterogeneity.

Stochastic Mechanical Mesoscale Modeling Of Cylindrical Cavities In Metallic Foams, Mujan N. Seif, Alexandre Martin, Matthew J. Beck

Mechanical Engineering Faculty Publications

Aluminum foam is a critical component of state-of-the-art micrometeoroid and orbital debris shielding. However, its randomly oriented constituent ligaments create significant variability in properties at different length scales. Previous efforts have thoroughly characterized the statistical implications of micro- to macro-scale-length transitions on the homogenized elastic behavior of damage-free, pre–micrometeroid and orbital debris (MMOD) strike structures. In this work, the properties of the residual material post MMOD impact are assessed by introducing cylindrical cavities representing the damage track. It was observed that configuring the cavity parallel to the through-the-thickness direction transformed a nominally isotropic foam into an anisotropic (transverse isotropic) material, …

Insights From And Future Directions For A Nationwide Science And Engineering Education Collaboration In Stratospheric Ballooning, Beth A. Covitt, Angela C. Des Jardins, Erick P. Agrimson, Jason T. Ash, Sean C.C. Bailey, Katelyn A. Barber, Mike J. Bastidas, Edgar A. Bering, Matthew T. Bernards, Anthony Choi, Nicholas B. Conklin, Jacqueline K.Q. Do, Montana Etten-Bohm, William F. Finney, James A. Flaten, Jeffrey M. Freedman, Rachel H. Humphrey, Eric P. Kelsey, Hunmin Kim, Christopher L. Lee, Wookwon Lee, Jared W. Marquis, Justin R. Minder, Jani M. Pallis, David J. Pawlowski, Chong Qiu, Joanna H. Rivers, Jason A. Ruszkowski, Jillian B. Schmidt, Thomas G. Sharp, Paul E. Slaboch, Suzanne W. Smith

Mechanical Engineering Faculty Publications

The Nationwide Eclipse Ballooning Project (NEBP) engaged 53 teams of students from across the United States to fly experiments on high-altitude balloons for the 2023 annular and 2024 total solar eclipses. By many measures, NEBP was a successful project. However, the teams did encounter challenges. To better understand what could be improved for similar future projects, this study engaged project partners in examining strengths, challenges, and recommendations across four topics: project structure, education and research approach, broadening participation, and funding. Analysis of the topics was completed through written comments followed by remote focus group discussions. The project director and evaluator …

Fiber-Reinforced Composites For Vaginal Tissue Engineering Applications, Samyuktha S. Kolluru, Abir Hamdaoui, Annabella M. Mascot, Siobhan S. Sutcliffe, Jerry L. Lowder, Michelle L. Oyen, Samantha G. Zambuto

Mechanical Engineering Faculty Publications

The vagina is a fibromuscular tube-shaped organ that plays critical roles in menstruation, pregnancy, and female sexual health. Vaginal tissue constituents, including cells and extracellular matrix components, contribute to tissue structure, function, and prevention of injury and pathology. However, much microstructural function remains unknown, including how the fiber-cell and cell–cell interactions influence macromechanical properties. A deeper understanding of these interactions will provide critical information needed to reduce and prevent vaginal pathologies. Our objective for this work is to design a novel tissue-mimicking biomaterial for vaginal tissue engineering, and characterize its biological and mechanical performance in the vaginal microenvironment. We successfully …

First Water-To-Ligand Substitution Dictates Co2+/Ni2+ Extraction Selectivity, Kailong Zhang, Yuxuan Zhang, Bin Ji, Rick Q. Honaker, Isabel C. Escobar, Jian Shi, Qing Shao

Mining Engineering Faculty Publications

Solvent extraction is a crucial technology for the large-scale recovery of critical metals. One key challenge is to develop ligands with high ionic selectivity, especially for ions with similar properties. Manipulating ionic solvation emerges as a viable approach to enhance the selectivity. However, such manipulation requires a thorough understanding of the thermodynamics underlying ligand-induced variation in ionic solvation. We investigated the thermodynamics governing the binding of two organophosphorus ligands (Cyanex 272 and D2EHPA) with Co²⁺ and Ni²⁺ at the aqueous-organic liquid–liquid interface using a combination of experiments and computations. UV-vis and IR spectroscopy confirmed that extraction induces solvation …

Adolescent Relationships With Digital Actors And Their Influence In A Classroom Setting: An Interpretive Case Study, Kerry A. Hancock

Theses and Dissertations--Curriculum and Instruction

In this post-COVID-19 society students are strongly influenced by their use of digital text and electronic devices. The assumption of the study was that if students spend time with devices and digital text that it might be possible for them to develop relationships with the non-human actors that exist as part of the learning environments in schools. This  interpretive case study rooted, in Posthumanist ideology, used Latour’s Actor Network Theory to approach data collection.

A comparative approach was adopted for this interpretive case study research and data were collected in three stages: initial classroom observation and analysis to determine the …

Industry To Classroom: The Role Of Academic Program Consultants In Building Self-Efficacy Among Occupation-Based Career And Technical Education Teachers, Erica L. Settelen

Theses and Dissertations--Educational Leadership Studies

Occupation-based career and technical education (CTE) teachers bring industry expertise to secondary classrooms but often begin teaching without traditional pedagogical preparation or familiarity with public school systems. In Kentucky’s New Teacher Institute (NTI), academic program consultants (APCs) provide program-area support to strengthen induction. Using the framework of self-efficacy and guided by Ivankova’s mixed methods action research (MMAR) framework, this study examined how occupation-based CTE teachers perceived APC engagement during induction and how APC-created asynchronous supports were experienced.

In the Reconnaissance Phase, a sequential Quantitative → Qualitative design included an initial survey followed by interviews. Survey results indicated midrange familiarity with …

Problem-Based And Practice-Driven: Designing For Engagement In An Online Educational Leadership Program, Owens G. Saylor

Theses and Dissertations--Educational Leadership Studies

Virtual professional learning has emerged as a flexible and scalable solution for developing educational leaders, particularly those navigating demanding roles and geographic barriers. However, these benefits often come at the cost of diminished engagement, interaction, and practical application to real-world leadership challenges. Without intentional design, virtual sessions risk becoming passive and disconnected, undermining their professional development value. This study responds to these challenges by exploring how a problem-based learning (PBL) approach can improve engagement in the virtual component of the Kentucky Leadership Rising (KLR) Aspiring Superintendent Workshop Series.

This mixed methods action research (MMAR) study examined participants’ perceptions of engagement …

Unveiling The Shadows: An Exploratory Study On Ghostwriting, Gray Markets, And The Ethics Of Contract Cheating, Micah Crawford

Theses and Dissertations--Educational Policy Studies and Evaluation

Contract cheating has become an increasingly complex challenge for higher education, particularly as digital platforms, global academic labor markets, and generative artificial intelligence reshape the production and detection of academic work. While much of the existing literature examines contract cheating from the perspectives of students, faculty, and institutions, less attention has been given to the individuals who produce ghostwritten academic work. This dissertation addresses that gap by exploring how shadow scholars understand their roles, ethical boundaries, and participation within the academic integrity ecosystem.

Using an exploratory qualitative design, this study draws on twelve semi-structured narrative interviews with six freelance academic …

The Operationalization Of Student Success: How Institutions And Divisions Of Student Affairs Define And Align Non-Academic Student Success With External Accountability Expectations, Madeline N. Trudeau

Theses and Dissertations--Educational Policy Studies and Evaluation

This qualitative multi-case study investigates how higher education institutions and their divisions of student affairs publicly discuss and define non-academic student success through their strategic planning, within the context of external pressures from state legislatures and accrediting bodies. Grounded in Organizational Learning Theory, Transition Theory, and Theory of Student Involvement and Engagement, this study analyzes the alignment and divergence between external policy expectations and internal institutional and divisional strategic plans.

The findings reveal a fundamental tension; while external stakeholders increasingly demand quantifiable outcomes tied to economic productivity - like post-graduate wages and employability metrics - divisions of student affairs continue …

A Historical Case Study Of The Effects Of The Coordinate Interagency Partnership Regulating International Students (Cipris) System And The Student Exchange Visitor Information System (Sevis) On Foreign Students Coming To The United States For Higher Education From 1990 To 2008, M. Ann Livingstone

Theses and Dissertations--Educational Policy Studies and Evaluation

The United States has welcomed foreign scholars and students since 1774, but their numbers increased dramatically after World War I, and again after World War II, as America became a world power leader and interest in the United States and its educational system and technological developments grew internationally. The Immigration and Naturalization Service (INS) was set up to oversee immigrants, visitors, and nonimmigrants who included students and diplomatic staff and families. This study deals with the changing laws and responsibilities of the INS during the period 1990 to 2008 to track foreign students in higher education, specifically with the introduction …