22505 research outputs found
Sort by
Caring for Your Heart During Survivorship After Pediatric Cancer: A visual education guide on chemotherapy-induced cardiotoxicity
No full textChemotherapy is an effective weapon in the fight against pediatric cancer. However efficient, treatment can lead to side effects that last long after a patient finishes their last round of chemotherapy. This thesis examines current research on chemotherapy-induced cardiotoxicity, a side effect of chemotherapy treatment caused by a class of chemotherapy drugs called Anthracyclines (such as doxorubicin and daunorubicin). While effective chemotherapy agents, these drugs have been known to cause late long-term heart damage when used to treat pediatric cancers such as Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (AML) and Pediatric Sarcoma. A written portion of this thesis project will examine the molecular mechanisms behind cardiotoxicity, risk factors, current drug and non-pharmacological preventative measures, and long-term follow-up care for patients as they transition into survivorship and adulthood. This paper will also outline a body of visual work created through collaboration with Dr. Brian Greffe, a pediatric oncologist (retired) and care team member at the HOPE Cancer Survivorship Program at Children’s Hospital Colorado in Aurora, Colorado. Resources on chemotherapy-induced cardiotoxicity exist, such as those created by the Children’s Oncology Group, but few focus on patient education through visual work. The combination of a printed education guide with access to interactive 3D media was created to provide childhood cancer survivors and their families with knowledge of this potential side effect as they transition into survivorship. Additionally, this project aims to equip patients and their families with knowledge for advocacy to find the necessary support and resources they may need during follow-up care. In doing so, the education guide aims to serve as a resource to inspire questions and conversation. By providing patients with knowledge, this project seeks to help patients feel informed for survivorship and enable them to make educated decisions about their medical care
Optimizing Traffic Signal Timings Using Real Time Data Analytics
No full textCity traffic jams have become a major challenge for contemporary cities, causing delays, increased fuel consumption, and other environmental impacts. Conventional traffic signal controlling systems usually depend on fixed or preset signal plans that are incompetent to adjust themselves with changing traffic conditions. Traffic signal timings are optimized across the intersection health of the system by processing real-time data analytics. Through real-time data analytics, traffic flow efficiency is improved while waiting time at signalized intersections is reduced. Using traffic real-time data like vehicle counts, vehicle types, time of day and day of the week to see howtraffic behaves under different situations. Statistical and analytical methods such as Chi- Square test and exploratory data analysis will be used to find out correlation between various traffic variables and congestion. This paper recommends adaptive signal timing strategies based on real-time traffic demand profiles gained from this investigation. The findings indicate a clear variation over time in traffic characteristics, supporting the limitations of fixed signal timings. The predictive models have undergone performance evaluation. It has been found that the Neural Network has the highest accuracy. The correlation coefficient is 0.98. The mean relative error is 0.0416. The value of R2 is 0.97. It outperformed the XGBoost, Random Forest, LSVM, and Linear Regression models. The data-driven approach for traffic signal optimizationwas predictive in nature and supports the effectiveness of adaptive real-time traffic control strategy
Predicting Undergraduate Fallout and Success
No full textUniversities need to uncover students who are likely to drop out early and do something about it. It should be easy to find and use this information. This thesis evaluated interpretable machine-learning models (MLMs) for predicting three final student outcomes including Dropout, Enrolled and Graduate, using solely demographic, administrative/financial and first-semester academic variables. Study employed publicly accessible Portuguese UCI student retention dataset (4,424 records) and incorporated end-of-Semester-1 feature window to prevent look-ahead leakage and align with actual advising cycles. We trained and compared models using stratified validation, explicit class-imbalance handling and decision-threshold optimization to make dropout detection most critical factor. Modified Random Forest performed best overall. When validation-selected operational threshold (τ* = 0.38) was set for testing, it delivered solid out-of-sample findings (Macro-F1 ≈ 0.68; Dropout-recall ≈ 0.70). Explain ability analyses indicated that first-semester academic momentum (allowed credits, mean grade and assessment counts) constituted primary source of risk. Status of tuition fees is helpful second indicator. This thesis concluded with an advisor-centric deployment strategy that integrated prioritized risk list with concise, factor-driven explanations to provide prompt and targeted interventions at conclusion of first semester
A Pilot Study Evaluating Child Resistant Closures in Pharmaceuticals in the Developing Nation of Ghana: Informing Global Paediatric Safety and Usability Standards
No full textDespite their proven effectiveness in preventing unintentional paediatric medication poisoning in high-income countries, the performance and usability of Child Resistant Closures (CRCs) remain underexplored in low and middle-income countries (LMICs).
To provide pilot data regarding the potential efficacy of using CRCs in LMICs, we conducted a study of the approach in a low-resourced region (Ghana, West Africa) by adapting testing protocols utilized in the United States (16 CFR Part 1700.20). The study utilized a convenience sample of children (n=50; 42-51 months) and adults (n=50; 50-70 years) to develop preliminary data related to the efficacy of a single design of CRC common to commercial markets in the US (ASTM IA).
Pilot testing results utilizing children were encouraging, as 98% of subjects (49 out of 50) were unable to open the CRCs. Of the 50 adult participants, 36 (72%) were able to open and close test samples within trial period. Although the sample size was not the 100 participants dictated under US protocol to officially report a Senior Adult Use Effectiveness (SAUE), our results were well below the required SAUE minimum of 90%.
While limited by sample size and regional scope, the study fills an important gap in knowledge by formally recognizing and documenting the disparate application of the human principle of justice in resource-limited regions compared to industrialized nations, provides preliminary evidence that CRCs could be an effective strategy in protecting children in these regions documented to have higher rates of mortality and morbidity, and also suggests that usability for adults should be explored further prior to implementation
Knowledge and Perception of Human Milk Donation Among Pregnant, Lactating, and Postpartum Women in Rochester, NY, and Near HMBANA Milk Banks
No full textHuman milk banks provide pasteurized donor milk for premature infants whose mothers are unable to produce sufficient amounts of milk, offering critical nutritional and immunological benefits for this high-risk population.1–4 Although 28 HMBANA-accredited milk banks operate in the United States, none are located within 4.5 hours of Rochester, NY. This study examined the knowledge and perceptions of human milk bank donation among pregnant, lactating, and postpartum women in Rochester, NY, and in communities near HMBANA-affiliated milk banks, and assessed if there is a correlation regarding the proximity of milk banks. A cross-sectional study design was used, and participants completed a 25-item survey, adapted from a Theory of Planned Behavior-based instrument assessing knowledge, attitude, subjective norms, perceived behavioral control, and intention to donate.5 Recruitment occurred through Facebook lactation and mother support groups near Rochester and the 28 U.S HMBANA-accredited milk banks, as well as in person at Rochester WIC clinics. The survey was open for three weeks (October 10th to October 31st, 2025), and 122 women participated. Knowledge differed significantly across ZIP code groups (p \u3c .001), with the highest scores among participants living neither in Rochester nor near a milk bank. Knowledge was positively correlated with total KANI scores (r =.289, p = .002) but was not associated with intention to donate or subjective norms. No significant differences between ZIP code groups were observed for attitude, subjective norms, intention to donate, or total KANI scores. However, several meaningful correlations emerged: higher subjective norms correlated with higher total KANI scores, pregnancy status, and number of children; and intention to donate was significantly associated with subjective norms. Participants residing near milk banks placed greater value on others’ opinions, and pregnant participants reported stronger subjective normative influences than non-pregnant participants. Prior donation experience or awareness of milk donation did not correspond to higher knowledge. While geographic differences were limited, the identified correlations highlight the need for targeted education to improve knowledge and understanding of human milk donation
Exploring the Experiences of Physically Challenged Students Enrolled in PATH-fit Courses: A Case Study
No full textThis qualitative case study explores physically challenged students’ experiences in PATH-fit courses within Philippine higher education, investigating their challenges and adaptive strategies. Through in-depth interviews with five students and two instructors in Pagadian City, researchers uncovered significant barriers, including exercise difficulties, physical discomfort, and social exclusion that profoundly impacted course participation. Despite facing substantial obstacles, students demonstrated remarkable resilience by developing innovative coping mechanisms such as proactive instructor communication, creative alternative activity engagement, and strategic leveraging of written assignments. Employing Resiliency Theory, the research challenged conventional disability perspectives, emphasizing that students’ true potential lies in psychological flexibility and problem-solving skills rather than physical capabilities. Key recommendations include developing flexible assessment methods, providing personalized learning alternatives, improving institutional infrastructure, and offering financial assistance. The study ultimately reveals that inclusive physical education requires a holistic approach, recognizing diverse capabilities, transforming potential barriers into opportunities for personal growth and educational engagement
Security Evaluation of Post-Quantum ML-DSA Implementations Against Software-Induced Fault Attacks
No full textQuantum computing is a form of computation that uses the principles of quantum mechanics to perform mathematical computations at a faster rate than classical computers. Although quantum computing is currently still in its early stages, if a general-purpose, large-scale, and fault-tolerant quantum computer were to be built, it would jeopardize the security of modern public-key cryptosystems. If these cryptosystems were broken, secure connections could not be authenticated, enabling Man-in-the-Middle (MitM) attacks, and digital messages could not be signed. All data sent over secured HTTPS and/or TLS connections would be vulnerable and potentially malicious since its origin and integrity could not be trusted. To prepare for this potential threat, the National Institute of Standards and Technology (NIST) created a Post-Quantum Cryptography (PQC) initiative to identify and develop a new set of quantum-resistant algorithms that can withstand the additional computing power quantum computers would provide. After three rounds of evaluation, NIST produced official standards in 2024 from the leading candidates in the PQC project with the intention that modern infrastructure would slowly migrate to these new algorithms and become quantum-resistant. However, while NIST performed extensive theoretical evaluation of these PQC candidates, theoretical security does not necessarily guarantee practical resilience. Latent vulnerabilities in software or hardware implementations can undermine critical security assumptions rendering these implementations insecure in practice, even if they are theoretically sound. Additionally, these vulnerabilities may be non-obvious in typical operation but can be unexpectedly invoked by various triggers. Furthermore, resistance to these implementation-level attacks was not a formal requirement during NIST standardization and remains an area of active research. This thesis contributes to the practical evaluation of emerging PQC standards by assessing the impact of fault attacks on recent open-source implementations of post-quantum digital signatures. In particular, this thesis focuses on fault attacks targeting the deterministic variant of CRYSTALS-Dilithium as implemented in OpenSSL v3.5.2. CRYSTALS-Dilithium is the primary digital signature algorithm selected by NIST for standardization due to its strong security and excellent performance. Additionally, open-source implementations are of particular interest due to their widespread availability and the transparency they provide, which enables community-driven development, security review, and evaluation. This thesis surveys recent literature on fault attacks targeting CRYSTALS-Dilithium, outlines a realistic web-based attacker model, and ranks each attack using a newly proposed risk framework which evaluates attacks based on severity and likelihood of success. Then, this thesis simulates the highest-risk attack using a modified version of OpenSSL to reliably reproduce the attack and demonstrate its viability in modern implementations. Finally, this work evaluates potential countermeasures to this attack, estimates their runtime overhead, and offers recommendations for improving resistance to such threats in cryptographic implementations. The experimental simulation presented in this thesis demonstrates that a substantial portion of the runtime of deterministic ML-DSA in OpenSSL v3.5.2 is susceptible to a fault attack identified by researchers Bruinderink and Pessl in 2018. This attack targets the signature generation process by inducing bit flips in intermediate internal variables, resulting in a malicious signature that leaks the private key. When both faulty and legitimate signatures are obtained, the attacker can solve a system of equations to recover the primary secret key and subsequently forge digital signatures. Such an attack compromises the security of ML-DSA and may be realized through known fault mechanisms such as Rowhammer, which exploit the layout of DRAM hardware to induce bit flips in adjacent memory regions. This thesis proposes verifying signatures before they are exposed as an effective countermeasure, enabling the early detection of malicious signatures, while incurring a minimal 18% runtime overhead. This overhead is substantially lower than the 84% to 400% overhead of implementing similar countermeasures in historical signature schemes such as ECDSA and Ed25519
The Power of a Formative Experiment in an Inclusion Science Education Classroom
No full textFormative experiments offer a novel approach to research educational interventions
in inclusion science classrooms. This research examined whether using a formative experiment design with an intervention called Peer-Assisted Learning Strategies (PALS) increased reading comprehension in grade-level biology text and science self-efficacy of students who had learning disabilities in reading in an inclusion biology classroom. Despite the small n, the results showed that there were statistically significant increases in the comprehension of grade-level biology text and science self-efficacy for the students with learning disabilities who participated in the study