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A machine learning based framework for predicting drug cardiotoxicity using a combination of ECG biomarkers and drug dosage data
No full textDrug-induced cardiotoxicity presents a significant challenge in clinical practice and drug clinical development, particularly with medications that modulate calcium, potassium, and sodium channels that influence cardiac electrophysiology. Clinical practice often relies on QTc prolongation alone as a predictor, which lacks specificity and may lead to excluding other safe therapeutic options. To address this limitation, this study integrates electrocardiogram (ECG) biomarkers with normalized drug dosage data to improve the accuracy of cardiotoxicity risk prediction using machine learning techniques. ECG features, including QT, QRS, RR, and PR intervals, were analyzed alongside normalized dosage data to account for dose-dependent cardiac effects. A physiologically driven risk scoring algorithm was developed to categorize cardiotoxicity severity, which was then used to train multiple machine learning models: convolutional neural networks (CNN), gradient-boosted trees (XGBoost and LightGBM), and multi-task neural networks (MTNN). Among the four models tested, CNN demonstrated perfect recall (1.000) and an ROC AUC of 0.995, indicating strong sensitivity to subtle ECG variations. However, CNN showed the lowest precision (0.488) and F1-score (0.655), reflecting a high false positive rate. In contrast, XGBoost achieved a strong overall balance, with an accuracy of 0.997, precision of 0.907, F1-score of 0.951, and a perfect ROC AUC (1.000), effectively capturing ECG and dosage interactions. LightGBM outperformed across most metrics, with the highest accuracy (0.998), precision (0.929), F1-score (0.963), and a perfect ROC AUC, making it a reliable model for confident classification. MTNN also showed excellent performance with high precision (0.927), recall (0.974), F1-score (0.950), and a perfect ROC AUC. These findings highlight the importance of integrating different ECG features with pharmacologic data in order to realize the significance of drug-induced cardiotoxicity risk. Evaluating the models’ strengths reflects different clinical needs, such as broad screening (CNN) to high-confidence risk classification (LightGBM). This approach advocates for earlier and more precise identification of proarrhythmic risk, enhancing patient safety and optimizing decision-making in clinical practice as well as in cardiovascular drug development
ASSOCIATIONS BETWEEN OBSERVANCE OF ORTHODOX JEWISH MOURNING RITUALS AND THE PSYCHOLOGICAL PROCESSES OF MEANING MAKING AND RELIGIOUS COPING FOLLOWING LOSS: A QUANTITATIVE STUDY
No full textWhile grief is a deeply individualized experience, research suggests that some coping mechanisms—such as meaning making—promote healthier psychological adjustment. Jewish mourning rituals may support meaning making, yet few studies have quantitatively examined this relationship. The present study investigated the association between observance of early Jewish mourning stages (i.e., aninut, levayah, and shiva) and both meaning making and adaptive religious coping. A sample of 60 Orthodox Jewish adults who had experienced the loss of a first-degree relative between one and five years prior to the start of the study completed measures of mourning observance, meaning making, and Jewish religious coping. Results revealed significant associations between several aspects of ritual observance and meaning making and coping. Specifically, aninut observance was significantly positively correlated with the Meaning of Significant Other subscale of the Meaning Making in Grief Scale (MMGS), shiva refrainment was significantly positively correlated with MMGS total score and meaning of significant other, and levayah observance was significantly positively correlated with scores on the Jewish Religious Coping Scale (JCOPE). Contrary to hypotheses, results indicated stronger associations between both aninut and levayah with meaning making than between shiva and meaning making. Additionally, shiva refrainment (i.e., abstention from prohibited activities) showed stronger positive correlations with meaning making as compared to active ritual performance. Findings from this study highlight the clinical utility of understanding culturally and religiously grounded mourning practices as potential pathways to meaning making. Mental health professionals working with Orthodox Jewish clients may benefit from exploring clients’ engagement with specific mourning rituals that support meaning making and religious coping
EXPLORING ELEMENTARY AND MIDDLE SCHOOL BUILDING LEADERS’ EXPERIENCES, PERSPECTIVES, AND STRATEGIES IN IMPLEMENTING, INTEGRATING, AND EVALUATING SOCIAL-EMOTIONAL LEARNING IN NORTHEASTERN UNITED STATES SCHOOLS
No full textIn this phenomenological qualitative study, I explored how school-building leaders’ perspectives, experiences, and knowledge impact the implementation and sustainability of social-emotional learning (SEL) programs in Northeastern U.S. schools. I conducted semistructured interviews with 10 elementary- and middle-school-building leaders to gain insights into their lived experiences and leadership practices related to SEL. Grounded in distributed-leadership theory (DLT), which emphasizes shared leadership, study results showed that all participants viewed SEL as essential to students’ well-being and academic success. However, leaders reported inconsistent implementation across classrooms and schools, accompanied by limited district support. Although schools promoted SEL in theory, participants noted a lack of resources and guidance, often leaving them to navigate SEL implementation independently. Key challenges included limited teacher training, lack of staff commitment, competing academic priorities, and limited resources. Despite these challenges, participants emphasized that sustainable SEL implementation requires strong structural support and shared vision in the school community. Through this study, I concluded that SEL should not be treated as an independent initiative but as a foundational pillar of education. Building leadership capacity, fostering inclusive practices, and creating sustainable systems were critical components for success. Recommendations include professional learning for all stakeholders, fostering positive and inclusive school climate, and aligning SEL with academic priorities. Study implications highlight the need for clear districtwide vision and structured support for SEL to ensure SEL is sustainable and equitable across schools. Insights support school leaders in using DLT to drive meaningful SEL integration
Gratitude and Personality: A Meta-Analysis
Full text linkThe purpose of this study is to explore the relationship between gratitude and personality through a comprehensive review of existing research and a meta-analysis of findings on the correlation between gratitude and the Big Five personality dimensions
Exploring Gender Disappointment: Social Stigma, Underlying Shame, and Grieving an Idealized Family… “Oh well, as long as it’s a healthy baby!”
Full text linkGender disappointment (GD) refers to the sadness parents feel when the sex of their child differs from their preference (Groenewald, 2016). While GD is a globally recognized phenomenon, research in the United States remains limited despite anecdotal evidence on social media and restrictive gender norms (Heise et al., 2019). This qualitative study explored the subjective experiences of GD in American mothers. Twelve biologically female participants, aged 18 and older, who experienced GD were recruited through convenience and snowball sampling. Semi-structured interviews conducted via video conferencing, averaging 40 minutes, were analyzed using grounded theory methodology (Auerbach & Silverstein, 2003). A member check validated the results. Six theoretical constructs emerged: 1) The Illusion of Control: Mothers’ Efforts to Control for Gender, Their Realizations of Powerlessness, and Dealing with What is; 2) Mothers Yearn for Empowerment of Girlhood, Strong Familial Relationships, and Lifelong Bonds through Raising Daughters; 3) Mothers Express Emotional Turmoil over Having Sons Resulting from Preexisting Beliefs, Gender Stereotypes, and a Perception of Males as Unfamiliar; 4) Why Not Me? The Emotional Impact of Societal Comparisons and Reminders of Unmet Gender Wishes on Mothers Having Sons; 5) Breaking the Silence: Mothers Need Support to Navigate the Guilt, Shame, and Stigmatization of Gender Disappointment; and 6) Mothers’ Journey of Grief toward Acceptance: Embracing the Duality of Desire and Reality. Findings highlight GD’s psychological challenges, the need for mental health support, reduced stigma, and trained medical professionals. This research aims to normalize GD, foster dialogue, and inspire therapeutic interventions to help mothers with GD
An Exploratory Study on the Usability of Distance Learning Technology in the U.S. Army Recruiting and Retention Command
Full text linkThis exploratory study investigates how integrating distance learning technologies within the U.S. Army impacts enlisted soldiers in terms of implementation, usability, and long-term career mobility. With internet-based education, active-duty enlisted personnel can pursue academic degrees from accredited military-affiliated institutions while simultaneously fulfilling operational duties, deployments, and daily training. The U.S. Army Recruiting Command has capitalized on this advancement by framing online education and digital accessibility as core components of its enlistment strategy. This approach is particularly relevant given that a significant proportion of new recruits originate from rural and economically disadvantaged areas, where access to higher education is often limited, and many rely on minimum-wage employment or public assistance. For many, the promise of tuition-free college education is a decisive factor in choosing military service. Attaining a Bachelor\u27s degree during one’s initial term can serve as a launchpad to broader civilian opportunities, offering a tangible pathway out of socio-economic stagnation. In this sense, the degree becomes more than a credential, representing an exit strategy from underserved communities. However, this dynamic introduces a strategic dilemma for the U.S. Army’s retention mission. While distance learning empowers soldiers academically and professionally, it may also reduce the incentive for reenlistment once educational goals are met. The Army’s long-term operational effectiveness relies heavily on retaining experienced personnel, especially those who have cultivated leadership skills and battlefield insight. Therefore, this exploratory study assesses whether the widespread adoption of digital education tools strengthens or undermines force recruitment and retention
Effect of Fe-Co Molar Ratios on Efficient CO₂ Hydrogenation to Light Olefins
No full textThe increasing concentration of greenhouse gases, particularly carbon dioxide (CO₂), is a major contributor to global warming and climate change. To address this issue, significant efforts have been made to catalytically convert CO₂ via hydrogenation. In this study, a series of Fe-Co organometallic complexes with varying Fe/Co molar ratios (5:1, 3:1, 2:1, 1:1, 1:2, 1:3, 1:5) were synthesized using solvent evaporation. The resulting samples underwent mild thermal treatment, yielding highly magnetic bimetallic catalysts. The catalysts were compressed to a uniform particle size and loaded into quartz tubes for evaluation. CO₂ hydrogenation was conducted in a flow bed reactor under controlled temperature and CO₂/H₂ flow conditions, with reaction products analyzed via online gas chromatography (GC). The results demonstrated that the Fe-Co catalyst with a 1:1 molar ratio exhibited the highest selectivity and conversion efficiency for CO₂ hydrogenation to light olefins. These novel magnetic bimetallic catalysts provide valuable insights into the role of Fe₃O₄ and Co₃O₄ in the reaction pathway for CO₂ hydrogenation to light olefins
How Will Primigravida Parents and Multigravida Parents Differ in Their Feelings About Pre-Test Group Genetic Counseling Sessions for Carrier Screening and Non-Invasive Prenatal Screening?
No full textThere are many populations that have a large need for the services of genetic counselling but due to factors such as ratio of genetic counselors to patients or lack of resources, the services are not widely available. In place of one-on-one genetic counseling visits, group genetic counselling sessions are an option in support of or in-place of these individual appointments. In this study we look at effectiveness of group prenatal genetic counselling sessions at the Naval Medical Center in San Diego and compare the implications of effectiveness of these group sessions from primigravida versus multigravida women who attend these sessions. At the conclusion of each genetic counseling group session the mothers took a survey to guide in their understanding about the content that was provided during the group session. In addition, women indicated whether they were primigravida or multigravida as well as provided insight into their feelings on the effectiveness and opinions on the group genetic counseling sessions. The results from this survey were used to make conclusions about group counseling as a method of healthcare by evaluating the data using a chi-squared test. The data from the survey was not able to find significance between primigravida and multigravida women who attended the group genetic counseling sessions. The lack of significant data may be due largely in part to the low number of respondents. The lack of significance of the data was able to provide insight into the effectiveness of the method group genetic counseling for pretest prenatal counseling
SECONDARY EDUCATORS’ PERSPECTIVES ABOUT THE INFLUENCE OF ARTIFICIAL INTELLIGENCE AS AN INSTRUCTIONAL TOOL IN SECONDARY EDUCATION
No full textAs Artificial Intelligence (AI) rapidly transforms various sectors of society, its implications for secondary education have become increasingly influential. This qualitative dissertation explores how educators in secondary education institutions on Long Island, New York, perceive the influence of Artificial Intelligence as an instructional tool. While Artificial Intelligence offers promise in enhancing lesson planning, differentiation, and teacher efficiency, as an instructional tool into the classroom. The influence of artificial intelligence as an instructional tool also raises significant questions related to student engagement, cognitive development, educational equity, and teacher preparedness. The purpose of this study was to examine these perceptions in order to inform responsible and equitable Artificial Intelligence implementation strategies in education. This study was influenced by Grounded Theory and Phenomenological approaches; the study employed a two-phase design. A survey was distributed to 208 secondary educators across multiple content areas, followed by interviews with six educators from English and Social Studies departments. The research addressed four sub-questions concerning educators’ views on Artificial Intelligence’s benefits and challenges, its impact on instructional practices, the role of professional development, and ethical considerations. The date analysis revealed a pattern of cautious optimism. While the majority of participants acknowledged Artificial Intelligence’s potential to reduce workload and support differentiated instruction, many expressed concerns about student overreliance on Artificial Intelligence, its effect on executive functioning, and its potential to widen educational inequities. Only 35.3% of respondents felt adequately trained to implement Artificial Intelligence in their instruction, while over 79% expressed a desire for further professional development. The study concluded that successful integration of Artificial Intelligence as an instructional tool into secondary education requires strategic planning, inclusive professional learning, ethical oversight, and a commitment to preserving the human elements of teaching. This research contributes to the growing discourse on Artificial Intelligence in education by focusing on teacher perspectives and offering recommendations to guide school leaders, policymakers, and instructional designers in shaping future-ready, equitable learning environments
MIDDLE SCHOOL TEACHERS’ INTEGRATION OF ARTIFICIAL INTELLIGENCE TOOLS AND ITS IMPACT ON LEARNING OUTCOMES IN A SUBURBAN SCHOOL DISTRICT
No full textGrounded in the Technology Acceptance Model (TAM), this study examined middle school teachers’ adoption of artificial intelligence (AI) tools, emphasizing how perceptions, instructional support, and integration strategies shape classroom use. The sample comprised 56 teachers across grades 6–8, representing multiple subject areas. Quantitative analyses revealed notable trends by teaching experience and subject specialization. Teachers with 0–5 years of experience reported the highest mean AI use scores, while those with more than 16 years of experience reported the lowest. Subject-specific differences were also observed, with mathematics teachers demonstrating the most favorable perceptions of AI tools and English teachers reporting the least favorable perceptions. Although the ANOVA results did not reveal statistically significant differences across groups, the observed trends suggest meaningful variation in AI adoption across both subject areas and teaching tenure. A multiple regression analysis further indicated that teachers’ Perceptions of AI Tools in General (PAITG), Perceptions of AI Tools on Student Performance (PAISP), and Support for AI Integration (SAIN) were significant predictors of AI Use (AIUN). Complementary qualitative findings reinforced these statistical results, emphasizing the critical roles of professional development, reliable infrastructure, and institutional support in fostering meaningful and sustained AI integration