Digital Commons Network^™

Enhancing Early Sepsis Detection: Outcomes Of An Educational Program In An Emergency Department, Courtney Mettes

Dissertations

Systemic inflammatory response syndrome progressing to sepsis presents a significant challenge in emergency departments (ED), where delayed recognition and treatment increase morbidity, mortality, and costs. This project evaluated whether implementing the Evaluation for Severe Sepsis Screening Tool (SSST) alongside an existing sepsis best practice advisory (BPA) could reduce the interval from sepsis BPA alert to initiation of lab work and treatment in adult patients (18 years and older). A quasi-experimental design compared retrospective control data (n = 81, Group 1) with prospective project data (n = 34, Group 2) over eight weeks. ED nursing staff received specific education on …

The Impact Of Artificial Intelligence On Leadership: A Systematic Literature Review Of Emerging Aspects And Organizational Effectiveness, Adrian Graca

European Management Studies

Purpose: In today’s working environment, constant change has become the norm. Various departments are undergoing transformations from traditional systems to those more suitable for a technology-driven environment. This systematic literature review investigates the evolving landscape of leadership strategies in the context of artificial intelligence integration within organizations. Technological advancements necessitate a transformation in leadership approaches to harness AI's potential effectively while addressing associated challenges such as ethical concerns and human-machine collaboration.

Design/methodology/approach: This research is a systematic literature review conducted using the PRISMA framework. Relevant academic publications were sourced from reputable databases, including Web of Science, Scopus, and EBSCO. A …

An Annotated Biobank Of Triple-Negative Breast Cancer Patient-Derived Xenografts Features Treatment-Naïve And Longitudinal Samples During Neoadjuvant Chemotherapy, Amanda L Rinkenbaugh, Yuan Qi, Shirong Cai, Jiansu Shao, Faiza Baameur Hancock, Sabrina L Jeter-Jones, Xiaomei Zhang, Emily Powell, Lei Huo, Rosanna Lau, Chunxiao Fu, Rebekah Gould, Petra Den Hollander, Elizabeth E Ravenberg, Jason B White, Gaiane M Rauch, Banu Arun, Clinton Yam, Alastair M Thompson, Gloria V Echeverria, Stacy L Moulder, W Fraser Symmans, Jeffrey T Chang, Helen Piwnica-Worms

Faculty, Staff and Student Publications

Triple-negative breast cancer (TNBC) that fails to respond to neoadjuvant chemotherapy (NACT) can be lethal. Developing effective strategies to eradicate chemoresistant disease requires experimental models that recapitulate the heterogeneity characteristic of TNBC. To that end, we established a biobank of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from the tumors of 75 patients enrolled in the ARTEMIS clinical trial (NCT02276443), including 12 longitudinal sets generated from serial patient biopsies collected throughout NACT treatment and from metastatic disease. Models were established from both chemosensitive and chemoresistant tumors, and nearly 30% of the PDX models were capable of metastasizing …

Optimizing Driving Waveforms To Enhance Inkjet Printing Speed, Chao Jan Sui, Wenchao A. Zhou

Mechanical Engineering Faculty Publications and Presentations

Inkjet printing has been extensively employed across various industrial applications due to its capability to produce high-resolution outputs and accommodate a diverse range of materials. However, its printing speed (volumetric printing rate or volumetric productivity) has remained a bottleneck for large-scale manufacturing. This study introduces a new strategy aimed at enhancing the speed of piezoelectric inkjet printing by optimizing waveform parameters. Expanding on our prior work, which analyzed the relationship between driving signal parameters and key factors like droplet volume and jetting frequency, we now focus on optimizing these parameters to maximize printing speed. To establish a fair comparison across …

Steep Decline In Diadema Antillarum Populations In Honduras’ Mesoamerican Barrier Reef (2014-2022) And Its Impact On Benthic Communities, Rebecca Cramp, Dan Exton, Max Dv Bodmer, Nathalie Lubbock, Miriam Reverter

School of Biological and Marine Sciences

Many Caribbean coral reefs shifted from coral to macroalgal-dominated communities following the die-off of the herbivorous urchin Diadema antillarum in the 1980s. Whilst most reefs remained algal-dominated, some have shown signs of coral recovery. This study compared benthic cover and D. antillarum populations (2014–2022) in two differently degraded reef systems in Honduras: Banco Capiro (Tela Bay) and Utila Island. In 2014, Banco Capiro had high coral cover (~ 59%) and D. antillarum densities (155 individuals/100 m ²), whereas Utila’s reefs had low coral cover (~ 17%) and low D. antillarum densities (2.5 individuals/100 m ²). By 2022, D. …

The Functional Efficiency Of Healing Gardens Elements And Its Impact On The Functional Aspect Of Hospitals, Menna Allah Hesham Mohammed, Heba Mohamed Abdou

Mansoura Engineering Journal

Communication with nature has a positive effect on human health and well-being in different civilizations all time. But technological development caused the production of purely functional buildings that are far from communicating with nature, although some buildings contain gardens to achieve communication with nature, their elements are poor. Therefore, healing gardens are considered one of the main elements to raise the efficiency of the functional performance of the health building because they contain the resting places and healing departments. Therefore, this study focuses on determining the functional criteria for the elements of the garden that must be considered when designing …

Therapeutic Radiation Drives Leptomeningeal Dissemination Of Medulloblastoma Through An Innate Immune Process, Carolina Nör, Kaitlin Kharas, Alex Rasnitsyn, Maria C Vladoiu, Nam Woo Cho, Jacob S Young, Felipe Nör, Ncedile Mankahla, Joonas Haapasalo, Kristiina Nordfors, Sara Rapic, Patryk Skowron, Raúl A Suárez, Alexander T Bahcheli, Oliver Ocsenas, Xin Chen, Shahrzad Bahrampour, Ali Momin, Lakshmikirupa Sundaresan, Winnie Ong, Liam D Hendrikse, Namal Abeysundara, Kyle Juraschka, Michelle Ly, Jonelle G Pallota, Tajana Douglas, Ning Huang, Hao Wang, Esta Mak, Lei Qin, Jessica Liu, Lily Shen, Betty Luu, Alex Manno, Sachin A Kumar, Laura K Donovan, Vernon Fong, Cory Richman, Craig Daniels, Livia Garzia, Jeremy N Rich, Cynthia Hawkins, Xiaochong Wu, Ralph Dacosta, Jüri Reimand, Xi Huang, Vijay Ramaswamy, David R Raleigh, Michael D Taylor

Faculty, Staff and Students Publications

Leptomeningeal metastases are the most important source of morbidity and mortality for medulloblastoma patients. Radiation of the entire brain is highly effective in the treatment and/or prevention of medulloblastoma leptomeningeal metastases. Infants treated on clinical trials with focal tumor radiation recur metastatically, whereas infants treated with only chemotherapy relapse locally. In murine medulloblastoma model systems, provision of a single dose of radiation to the tumor drives leptomeningeal dissemination. An inflammatory response after radiation-induced tumor cell death recruits a variety of immune cells. Inflammation opens the local blood-brain barrier, allowing intravasation of medulloblastoma cells. Experimental induction of inflammation with lipopolysaccharide drives …

Electrochemical Breath Sensors In Medical Diagnostics: Emerging Trends And Future Directions, Natalie E. Strom, Courtney J. Weber, Olja Simoska

Faculty Publications

With the rising prevalence of metabolic diseases, infections, and mental health disorders, there is a growing demand for noninvasive diagnostic tools that enable early detection and continuous health monitoring. In this context, exhaled breath biomarkers provide insight into physiological and pathological processes. Electrochemical breath sensors (EBSs) have emerged as a promising platform for rapid, real-time, and cost-effective disease tracking via the detection of volatile breath biomarkers, such as NH₃, NO, and CO₂. Recent advancements in electrode materials, biological recognition elements, and sensor architectures—spanning nanomaterials, enzymes, aptamers, and molecularly imprinted polymers—have enhanced the analytical performance of EBSs. …

Electrochemical Breath Sensors In Medical Diagnostics: Emerging Trends And Future Directions, Natalie E. Strom, Courtney J. Weber, Olja Simoska

Faculty Publications

With the rising prevalence of metabolic diseases, infections, and mental health disorders, there is a growing demand for noninvasive diagnostic tools that enable early detection and continuous health monitoring. In this context, exhaled breath biomarkers provide insight into physiological and pathological processes. Electrochemical breath sensors (EBSs) have emerged as a promising platform for rapid, real-time, and cost-effective disease tracking via the detection of volatile breath biomarkers, such as NH₃, NO, and CO₂. Recent advancements in electrode materials, biological recognition elements, and sensor architectures—spanning nanomaterials, enzymes, aptamers, and molecularly imprinted polymers—have enhanced the analytical performance of EBSs. …

Advancing Power System Reliability And Security With Efficient And Resilient Graph Neural Network Frameworks, Seyed Hamed Haghshenas

USF Tampa Graduate Theses and Dissertations

Enhancing the reliability and security of smart grids is critical for ensuring their seamless operation and resilience against disruptions. The increasing integration of distributed energy resources, advanced measurement devices, and cyber-physical elements introduces both opportunities and challenges for grid management. While these advancements provide enhanced visibility and operational control, they also expose the grid to vulnerabilities from cyber-physical stresses, such as cyber-attacks, equipment failures, and fluctuating power demands. Traditional methods for reliability assessment and threat detection often rely on model-based approaches that struggle to adapt to the complexity and dynamic nature of modern smart grids. These limitations necessitate novel data-driven …

A Multiomics Recovery Factor Predicts Long Covid In The Impacc Study, Gisela Gabernet, Jessica Maciuch, Jeremy P Gygi, John F Moore, Annmarie Hoch, Caitlin Syphurs, Tianyi Chu, Naresh Doni Jayavelu, David B Corry, Farrah Kheradmand, Lindsey R Baden, Rafick-Pierre Sekaly, Grace A Mccomsey, Elias K Haddad, Charles B Cairns, Nadine Rouphael, Ana Fernandez-Sesma, Viviana Simon, Jordan P Metcalf, Nelson I Agudelo Higuita, Catherine L Hough, William B Messer, Mark M Davis, Kari C Nadeau, Bali Pulendran, Monica Kraft, Chris Bime, Elaine F Reed, Joanna Schaenman, David J Erle, Carolyn S Calfee, Mark A Atkinson, Scott C Brakenridge, Esther Melamed, Albert C Shaw, David A Hafler, Alison D Augustine, Patrice M Becker, Al Ozonoff, Steven E Bosinger, Walter Eckalbar, Holden T Maecker, Seunghee Kim-Schulze, Hanno Steen, Florian Krammer, Kerstin Westendorf, Bjoern Peters, Slim Fourati, Matthew C Altman, Ofer Levy, Kinga K Smolen, Ruth R Montgomery, Joann Diray-Arce, Steven H Kleinstein, Leying Guan, Lauren Ir Ehrlich

Faculty, Staff and Students Publications

Background: Following SARS-CoV-2 infection, approximately 10%–35% of patients with COVID-19 experience long COVID (LC), in which debilitating symptoms persist for at least 3 months. Elucidating the biologic underpinnings of LC could identify therapeutic opportunities.

Methods: We utilized machine learning methods on biologic analytes provided over 12 months after hospital discharge from more than 500 patients with COVID-19 in the IMPACC cohort to identify a multiomics “recovery factor,” trained on patient-reported physical function survey scores. Immune profiling data included PBMC transcriptomics, serum O-link and plasma proteomics, plasma metabolomics, and blood mass cytometry by time of flight (CyTOF) protein levels. Recovery factor …

Fda Approval Of Artificial Intelligence And Machine Learning Devices In Radiology: A Systematic Review, Ram Sivakumar, Brian Lue, Shinjini Kundu

2020-Current year OA Pubs

No abstract provided.

Muscle Fatigue Arising Intrinsically From Sur2- But Not Kir6.1-Dependent Gain-Of-Function In Cantu Syndrome Mice, Rosa Scala, Maya Mukadam, Yuezhou Chen, Courtney Frazier, Nathaniel W York, Robert C Tryon, Gretchen A Meyer, Colin G Nichols

2020-Current year OA Pubs

Cantu syndrome (CS) is a rare disease caused by gain-of-function (GOF) mutations of Kir6.1 or SUR2 subunits of ATP-sensitive potassium (KATP) channels. CS patients with SUR2 and Kir6.1 variants display a similar constellation of symptoms, including muscle weakness and fatigue. The effects of CS mutations on skeletal muscle KATP channels, and any consequent direct effects on contractility, are currently unclear. Here, we used two knock-in mouse models of CS, respectively, carrying GOF mutations Kir6.1[V65M] or SUR2[A478V], to assess KATP channel properties and contractility in isolated fast-twitch extensor digitorum longus (EDL) and slow-twitch soleus (SOL) muscles. Electrophysiological recordings in isolated myofibers …

Abdominal Ultrasound Image Dataset For Organ Classification And Disease Detection, Sifat Zina Karim

Research Data

This is a dataset of Ultrasound (US) images of abdominal organs. US imaging is widely accessible and a very common diagnostic tool, as it is non-invasive and does not involve radiation risk. This dataset was curated solely for research in deep learning, with potential applications in supervised, semi-supervised, and unsupervised learning to support disease detection in resource-constrained settings.

The dataset comprises 5,468 unique images organized into ten anatomical categories: Abdominal Aorta (0), Gallbladder (1), Hepatic Vein (2), Kidneys (3), Liver (4), Ovaries (5), Pancreas (6), Portal Vein (7), Spleen (8), and a composite Pelvic Urinary/Reproductive category (9), comprising the Urinary …

Effects Of Code Scaffolding In Increasing Student Confidence In Programming Cryptography, John Denny

LSU Master's Theses

Cryptography is essential for secure communications, and new threats require more students willing to program and interact with cryptographic systems. Previous research is focused on tools for teaching these systems at a high level, teaching through attacks against these systems, and proper use of these systems in software development. In this paper, we seek to design a workshop to use scaffolded Python code to teach how these cryp- tographic systems are designed. We explore the use of code scaffolding for students to program an example implementation of the McEliece crypto- graphic system to build confidence in working with these systems. …

Integrating Augmented Reality (Ar) Into Industrial Engineering Education: Supporting Assembly Line Operations In Advanced Manufacturing Laboratory, Fidan Abdullayeva

LSU Master's Theses

The rapid development of innovative technology underscores the importance of preparing students to meet industry expectations. This study aims to design, develop, and integrate Augmented Reality (AR) applications into Industrial Engineering (IE) education, specifically within LSU’s IE 2400 System and Work Methods course. The research incorporates technology like Microsoft HoloLens 2 into laboratory exercises. It seeks to enhance students’ comprehension and visualization of complex industrial systems and concepts, while familiarizing them with AR technology’s potential in the manufacturing industry. The AR application features functionalities tailored to support specific roles. These include AR-enhanced assembly manuals for Assemblers and quality inspection tools …

Utilizing A Virtual Firewall Appliance For Introducing And Reinforcing The Concepts And Implementation Of Devices To Improve Security In A Computing Environment, Stanley Mierzwa, Christopher Eng

Center for Cybersecurity

The educational realm of higher education cybersecurity curriculum continues to evolve to provide more opportunities for experiential hands-on and work role-related practical applications of technology solutions. Gaining greater competencies is quickly becoming a normal requirement for such programs that are designated by the National Security Agency Center of Academic Excellence programs. The work roles of cybersecurity include a variety of knowledge, skills, and abilities, depending on the category of the activity or task. Firewalls have been a staple cybersecurity, network security, and information security device and strategy to protect organization networks and computing environments. This paper will provide details and …

Mathematical Modeling And Optimization Of Polymer Cold Spray Deposition For Enhanced Efficiency, Okikiola Ganiu Agbabiaka

Theses and Dissertations

Cold spray (CS) is a promising additive manufacturing technique for various industries, including aerospace and automotive. However, the application of CS to polymers presents unique challenges due to their inherent properties and complex deposition mechanisms. This study addresses critical knowledge gaps in polymer cold spray processes, focusing on optimizing parameters for enhanced deposition of polyvinyl alcohol (PVA) and polyamide-6 (nylon 6). Through a comprehensive three-stage experimental approach, the effects of gas temperature, feed rate, standoff distance, gas pressure, raster speed, particle size, and crystallinity on deposition efficiency was investigated. Utilizing advanced design of experiments methodologies, including a response surface methodology, …

Optimization Of Rheological Models Using Machine Learning-Based Surrogates, Sourav Saha

LSU Master's Theses

This study addresses the challenge of accurately modeling flows of complex, multiphase media through fluid machines, where highly viscous, compressible, and shear-thinning behavior of the medium complicates the construction of predictive models. Such media include slurries, biomass, foods, and other materials of high value and societal importance. A high-fidelity CFD model of a screw-type fluid machine with an outlet flow restriction is developed. The flowing medium is treated as a single-phase, compressible, non-Newtonian fluid. The model incorporates a non-linear pressure-dependent density model and a strain-rate-dependent viscosity law (Cross power law). A parametric study is conducted by varying key rheological parameters …

Impact Of Physiological And Environmental Variation On The Behavioral Response Of The Two Biological Control Agents Of The Emerald Ash Borer To Host-Associated Odors, Vanshika Jindal

LSU Master's Theses

Emerald ash borer (Agrilus planipennis Fairmaire; EAB) is an invasive pest that threatens ash trees (Fraxinus spp.) throughout North America and Europe. Since its introduction to North America, EAB has killed hundreds of millions of trees, resulting in severe ecological and economic damage exceeding 10 billion US dollars. Classical biological control involves the introduction of natural enemies from the native range of pests to manage their populations. Specialist parasitoid wasps have been released to reduce the populations of EAB. Detection and response to long-range attractants associated with EAB is critical for the location and parasitism by classical biological …

Lithological Modeling And Aquifer Characterization Of The Coastal Lowlands Aquifer System In Texas, Emmanuel Egyin Hayford

LSU Master's Theses

The Texas Coastal Lowlands Aquifer System (CLAS) is a crucial water resource for the Gulf Coast, serving millions through municipal, agricultural, and industrial supplies. However, its sustainability is increasingly threatened by factors such as population growth, saltwater intrusion, land subsidence, and climate change. A significant limitation is the absence of a comprehensive, data-rich, three-dimensional lithologic model that accurately represents the intricate structure and geometry of the aquifer. Existing models are overly simplistic, treating the hydrogeologic unit as laterally uniform and failing to capture its true hydrogeologic complexity. This study addresses this gap by developing the first high-resolution 3D lithologic model …

Integrative Proteogenomics And Forward Genetics Reveal A Novel Mitotic Vulnerability In Triple-Negative Breast Cancer, Nicholas J Neill, Shankha Satpathy, Karsten Krug, Jitendra K Meena, Nivetha Ramesh Babu, Cheyenne Calderon, Desmon Reed, Marcus J Weber, Lacey E Dobrolecki, Alaina Lewis, Christina Sallas, Meenakshi Anurag, Kimberly R Holloway, Chen Huang, Suhas Vasaikar, Maria F Cardenas, Beom-Jun Kim, Doug W Chan, Shayan C Avanessian, Siddhartha Tyagi, Mayra Orellana, Sufeng Mao, Heyuan Li, Fade Gong, Sarah J Kurley, Kristen L Meerbrey, Calla M Olson, Amritha Nair, Tingting Sun, Hsiang-Ching Chung, Elizabeth A Bowling, Jarey H Wang, Pengju Zhang, Peng Xiao, Duxiao Yang, Fabio Stossi, Mei-Yin C Polley, Alexander B Saltzman, Filip Mundt, D R Mani, Michael A Gillette, Susan G Hilsenbeck, George Miles, Carolina Gutierrez, C Kent Osborne, Charles Y Lin, Nathanael S Gray, Jinpeng Sun, David A Wheeler, Charles M Perou, Anna Malovannaya, Michael T Lewis, Bing Zhang, Matthew J Ellis, Steven A Carr, Thomas F Westbrook

Faculty, Staff and Students Publications

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with few effective targeted therapies. Taxanes and other microtubule-targeting agents (MTAs) are frontline chemotherapies for TNBC; however, the molecular pathways that cause TNBC taxane sensitivity are largely unknown, preventing selection of taxane-responsive patients and development of more selective therapeutic strategies. In this study, we identified tumor-selective vulnerabilities in TNBC harboring inactivation of the tumor suppressor PTPN12 by integrating proteogenomic characterization and synthetic lethality screening. We discovered that PTPN12 inactivation drives mitotic defects through aberrant hyperactivation of the ubiquitin ligase complex APCFZR1, a critical regulator of the cell cycle. Consistent …

Educational Policies Committee Agenda November 6, 2025, Utah State University

Educational Policies Committee

• Approval of Minutes - October 2, 2025
• Subcommittee Reports
• Curriculum Subcommittee
• Academic Standards Subcommittee
• General Education Subcommittee
• Other Business
• Adjourn: 4:00 pm

Experts’ Validation Of The Fundamental Cybersecurity Competency Index (Fcci) Using A Commercial Cyber Range Through Human-Generative Artificial Intelligence (Genai) Teaming, Dariusz Witko, Yair Levy, Catherine Neubauer, Greg Simco, Laurie P. Dringus, Melissa Carlton

Journal of Cybersecurity Education, Research and Practice

The increasing volume of cyber threats, combined with a critical shortage of skilled professionals and rising burnout among practitioners, highlights the urgent need for innovative solutions in cybersecurity operations. Generative Artificial Intelligence (GenAI) offers promising potential to augment human analysts in cybersecurity, but its integration requires rigorous validation of the fundamental competencies that enable effective collaboration of human-GenAI teams. This research study employed a mixed-methods research project designed to evaluate human-GenAI teams, emphasizing the role of expert consensus in shaping the experimental assessment of the Fundamental Cybersecurity Competency Index (FCCI) in a commercial cyber range. We engaged 20 Subject Matter …

Improving The Health Of Older Adults Through Access To Wellness Facilities, Rose Hayes, Riley Kimmel, Olivia Beam, Michele Shaw

NURS 404/406 Research & Info Management

PICOT Question: How does access to wellness facilities affect the health of the elderly?

Newsletter 2025.11.03, Fcrh Honors Program

What's Going On, Honors? (2025-26)

No abstract provided.

A Temperature-Sensitive Crispr-Cas12a System For Sterile Insect Technique, Christina Nguyen, Ahmed Idowu Omotayo, Sara Sanz Juste, Xuechun Feng, Víctor López Del Amo

Faculty, Staff and Student Publications

The sterile insect technique (SIT) reduces population numbers by releasing sterile males that produce non-viable progeny. Specifically, CRISPR/Cas9-based precision-guided SIT (pgSIT) generates sterile males through genetic crosses of two transgenic lines: a Cas9 strain and a guide RNA (gRNA) strain targeting male sterility and female viability or infertility. However, pgSIT requires separate maintenance of the two lines and sorting to obtain sterile males, creating possible challenges for scaling. To overcome this, we propose using Cas12a nuclease, which is inoperative at lower temperatures but active at higher temperatures. Here, we develop a Cas12a-based pgSIT system involving a single strain containing both …

Developing Middle School Students’ Systems Thinking In Earth Science Through Dynamic Simulations: The Case Of The Rock Cycle, Nicole Panorkou, Amanda Provost, Gabriella Migliore

Department of Mathematics Faculty Scholarship and Creative Works

In this paper, we discuss the development of students’ systems thinking about the rock cycle as they interact with an instructional module that includes three interactive simulations and accompanying questioning. We present the reasoning of six students from a whole-class design experiment in a sixth-grade classroom to describe how students’ systems thinking may be constructed and reorganized through activity with our design. Our findings highlight a framework of students’ systems thinking about the rock cycle that builds and expands prior work to specific sub-components. We also discuss an emerging framework for supporting students’ systems thinking through careful design of simulation …

Non-Reciprocal Coupling Of Minimal Active Colloids Under Confinement: Rotating Ferromagnetic Janus Particles Near Boundaries, Amrutha Raghu

LSU Doctoral Dissertations

Active colloids are microscopic particles that convert energy at the single-particle level into sustained motion and dynamically evolving assemblies. Their ability to transform continuous energy input into controlled motion opens new frontiers in microrobotics, adaptive materials, and targeted transport. Yet, achieving efficient propulsion at the microscale remains fundamentally challenging because viscous forces dominate while inertia becomes negligible. Unlike macroscopic systems that sustain propulsion through momentum, active colloids must harness non-reciprocal interactions with the surrounding fluid to generate persistent, time-irreversible motion. Studying minimal active systems—the simplest realizations that still capture the essential physics—provides a powerful route to uncover the non-equilibrium principles …

Practical Real-Time Permanent Magnet Energy Spectrometer Using A Diode Array For Therapeutic Electron Beam Tuning And Quality Assurance, Mason W. Heath

LSU Doctoral Dissertations

Purpose: Develop a practical, real-time permanent magnet electron energy spectrometer and evaluate it for beam tuning and quality assurance (QA) of therapeutic electron beams.

Methods: Aim 1: A 0.55 T permanent magnet was coupled to Sun Nuclear SRS MapCHECK® PC boards, providing two interlaced diode arrays. Detector response, R_meas(z_diode) versus diode position z_diode, was extracted from raw diode array readings, correcting for diode sensitivity and other factors. Using Monte Carlo (MC) computed, monoenergetic detector response functions, a curve-fitting algorithm extracted the energy spectrum, from R_meas(z_diode). The energy spectra for 7-20 …