Parameter Estimation of Eccentric Binary Black Holes using Targeted Numerical Relativity Simulations

Gravitational wave events detected by the LIGO-Virgo-KAGRA (LVK) collaboration are the result of compact binary mergers which produce gravitational wave (GW) emission. The observed waveform carries information about the source properties, such as masses, spins, and orbital eccentricity. Events harboring eccentricity upon entrance of the LVK sensitivity band at 10 Hz are believed to have been formed through dynamical channels, where the binary has interacted with other astrophysical objects leading to a merger faster than an isolated binary. Therefore, the identification of eccentric gravitational wave events and accurate determination of their parameters is vital to understanding the population of binary black holes that form and merge dynamically. In consideration of this, we have analyzed LVK gravitational wave events that have shown evidence of eccentricity, from both the literature and our own analysis using the effective-one-body model TEOBResumS, and confronted them independently with an analysis using full numerically generated waveforms from our bank of nearly two thousand simulations of binary black holes. We have used RIFT for Bayesian parameter estimation for both the model-based and numerical relativity (NR) analyses, where results from the model-based analysis are used to generate new targeted NR simulations in the highest likelihood region of parameter space as determined by the model-based analysis. Using the full bank of simulations (including the targeted simulations) we found through a kernel density estimate of the RIFT produced posteriors that GW200208_22 favors eccentricities e20 = 0.198(+0.119/−0.180) upon entering the LVK sensitivity band at 20 Hz within a 90% credible interval. Due to our method of generating targeted simulations at the intrinsic parameters of peak likelihood models, we have found that numerical relativity waveforms return a general improvement of likelihood for waveforms of the same intrinsic parameters. For GW200208_22 we find a new peak likelihood waveform, compared to model-based analysis, with an estimated eccentricity at 20 Hz, e20 = 0.200, thus reinforcing the eccentric hypothesis of the binary. We have also used our full bank of numerical waveforms on GW190620 finding that the KDE estimate favors eccentricities at 10 Hz in e10 = 0.190(+0.046/−0.186). However, new specifically targeted simulations will be required to narrow this eccentricity range

A Novel Nephron: 3D Visualization of Glomerular Filtration in the Kidney

Renal physiology, particularly the process of glomerular filtration, remains one of the most conceptually challenging topics in medical education due to its microscopic scale, dynamic pressure relationships, and structural complexity. Understanding how plasma passes through the glomerular filtration barrier requires spatial reasoning across multiple levels—from the gross anatomy of the kidney to the ultrastructure of capillaries, podocytes, and the glomerular basement membrane. This thesis addresses these challenges through the development of a scientifically accurate three-dimensional (3D) animation that illustrates glomerular filtration within its anatomical and physiological context. Designed as a visual teaching aid, the animation aims to improve comprehension of renal microanatomy, demonstrate the functional relationship between structure and process, and depict both normal and pathological filtration dynamics.  Development began with an extensive review of primary anatomical and physiological sources, including Brenner and Rector’s The Kidney (9th ed.) and Gray’s Anatomy: The Anatomical Basis of Clinical Practice (41st ed.), supplemented by recent research on glomerular barrier function. Conceptual sketches synthesized spatial relationships and established consistent color conventions before 3D modeling. Anatomical assets—including the glomerular capillary tuft, podocytes, Bowman’s capsule, and renal tubules—were primarily sculpted in ZBrush, while Autodesk Maya was used for animation and rendering. Procedural systems such as MASH, nParticles, and lattice deformers simulated blood flow, filtrate movement, and barrier disruption. Final compositing and narration were completed in Adobe After Effects, integrating narration, labeling, and sound design to create a cohesive visual narrative.  The completed animation presents glomerular filtration from both normal and pathological perspectives, visualizing the delicate balance of forces and structures that sustain renal function. By combining anatomical accuracy, educational design, and aesthetic clarity, the project transforms an abstract physiological process into a clear and tangible experience. This work demonstrates how biomedical visualization can enhance engagement and comprehension in renal physiology education while underscoring the broader potential of 3D animation as a tool for teaching complex biological systems

AR Bubble Car: A Cross-Vehicle Visual Social System for Autonomous Mobility

AR Bubble Car argues that in L4/L5 autonomous mobility, or high to fully automated driving, the car should be understood not only as a transportation device but also as a visible social interface in public space. As driving becomes less central, the role of the vehicle shifts from control and movement alone toward passenger experience, expression, and communication. In response, AR Bubble Car proposes a transparent visual bubble around compatible vehicles, allowing passengers to share lightweight content through window-based AR. Rather than treating the car as a private entertainment container, the system explores how vehicles might become moving social nodes on the road. This thesis develops that position through research on non-driving activities, passenger behavior, motion sickness, external vehicle communication, and in-vehicle AR, and then critically examines the proposal through questions of feasibility, risk, limitation, and criteria for success

Assessing Readiness, Perceptions, and Behaviors of Midlife Adults to Adopt a Dietary Pattern Associated with Cognitive Benefits

Objective:  To explore the barriers and facilitators for following a brain-healthy dietary pattern by assessing readiness, cognitive dietary adherence, eating competence, quality of life, and health beliefs in midlife adults. Design: Quantitative cross-sectional online survey. Participants: Adults aged 30-60 years (N=189) recruited through social media, flyers, email, and text. Main outcome measures: Readiness to adopt a brain-healthy dietary pattern, eating competence, health beliefs, quality of life, and dietary adherence to a brain-healthy pattern such as the MIND diet. Analysis: Descriptive statistics, ANOVAs, Chi-Square, and correlations were conducted to explore associations among readiness, eating competence, health beliefs, quality of life, and dietary adherence. Results:  Of 189 participants, most were unaware of eating for brain health. Readiness to adopt a brain-healthy diet was associated with higher MIND diet scores with those unaware or not interested reporting the lowest scores (10.0 +/- 2.8 vs 7.7 +/- 2.1 vs 7.6 +/- 2.2; P\u3c 0.001), greater eating competence in those interested compared to those unaware or not interested (35.6 +/- 7.3 vs 29.5 +/- 8.2; P=0.008), lower perceived barriers than both those unaware/not interested or contemplating (6.5 +/- 2.8 vs 8.6 +/- 2.6 vs 9.9 +/- 2.0; P\u3c 0.001), greater perceived benefits (14.0 +/- 1.4 vs 12.4 +/- 2.2; P=0.02), and greater self-efficacy (9.4 +/- 0.7 vs 8.2 +/- 1.7 vs 7.7 +/- 1.8; P\u3c 0.001). MIND diet scores were positively associated with eating competence(r=0.4; P\u3c 0.001), quality of life (r=0.3, P\u3c 0.001; r=0.2, P=0.002), and self-efficacy(r=0.3; P\u3c 0.001) and negatively associated with perceived barriers(r=-0.5; P\u3c 0.001).  Conclusion and implications:  This study identified barriers and facilitators for following a brain-healthy dietary pattern, such as the MIND diet, among midlife adults. Many participants were unaware of the connection between nutrition and cognitive health, highlighting a need for targeted education. Associations among readiness, eating competence, health beliefs, and diet quality suggest focal points for improving awareness and adoption of brain-healthy eating. These findings demonstrated the value of exploring this topic and provide guidance for future studies of larger and more diverse samples

Engineering Human Microphysiological Models to Investigate Bacterial Extracellular Vesicle–Driven Endothelial and Blood–Brain Barrier Dysfunction

Pathogenic bacterial extracellular vesicles (BEVs) are nanoscale particles derived from bacteria that contain pro-inflammatory cargo. During bacterial infections, BEVs provoke the host inflammatory response and may cause widespread damage. Furthermore, antibiotic treatment can boost BEV production and thereby increase the number of toxic signals traveling through the circulatory system. This is especially dangerous in brain blood vessels since evidence suggests that BEVs may destabilize the protective blood–brain barrier (BBB), resulting in neuroinflammation associated with cognitive decline and development of neurological disorders. Our understanding of BEV interactions with the host remains limited, necessitating the development of in vitro models to better understand their effects on human cells. Our work demonstrates that antibiotics modulate production of Escherichia coli–derived BEVs as well as packaging of pro-inflammatory cargo in a manner dependent on the bacterial strain and the class of antibiotics. These changes have pronounced effects on activation of human endothelial cells, causing increased expression of surface adhesion molecules that can attract immune cells and promote their transit from blood into surrounding tissues. Our identification of specific toxins incorporated in the BEVs may prove useful for future attempts to block their stimulatory effects. We model BBB interactions with BEVs using a microphysiological system featuring an ultrathin porous silicon nitride membrane. Human stem cell–derived brain microvascular endothelial cells demonstrate sensitivity to BEVs but still maintain a functional barrier after exposure. However, BEVs can indirectly disrupt the BBB by increasing the production of pro-inflammatory signals from immune cells. In other words, microphysiological models require an immune component for accurate assessments of BEV–initiated damage to the BBB. In the future, this work may serve as a basis for modeling therapeutic approaches to mitigate the effects of BEV–driven damage to blood vessels and brain tissues

A Pilot Study Evaluating Child Resistant Closures in Pharmaceuticals in the Developing Nation of Ghana: Informing Global Paediatric Safety and Usability Standards

Despite 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

Call For Manuscripts

The Journal of Science Education for Students with Disabilities is a peer-reviewed, open access, multi-disciplinary online journal with an international focus. We publish articles that reflect the best of research and practice related to inclusive science education, including works submitted by science and special education researchers, teacher educators, and teachers. Interesting topics have included innovative curricular ideas, instructional adaptations, research-based modifications, best practices, and management strategies in science education. JSESD adopts the philosophical perspective that all students can achieve in science, and that science benefits from the full participation of all students

Knowledge and Perception of Human Milk Donation Among Pregnant, Lactating, and Postpartum Women in Rochester, NY, and Near HMBANA Milk Banks

Human 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

Machine learning-based determination of sex-related bladder cancer biomarkers

Bladder cancer exhibits sex-specific behavior, occurring more frequently in males but progressing to advanced stages more commonly in females. The activation of sex hormone receptors may explain these differences, but the exact genetic drivers remain poorly understood. Furthermore, current bladder cancer biomarkers have inconsistent sensitivities and specificities in practice, making early diagnosis a challenge. This study approaches bladder cancer biomarker discovery through machine learning techniques on gender and disease-stratified RNA-seq data. Training sets limited to differentially expressed genes were subjected to four different feature selection methods: differential gene expression analysis adjusted p-value, recursive feature elimination with support vector machine, logistic regression, and an optimized random forest procedure. Gene panels were compared and aggregated across selection strategies and crossvalidation folds to identify robust biomarkers for sex-specific bladder cancer development and progression. When applied to unseen datasets and limited to 50 genes or less, male and female-specific panels achieved areas under the receiver operating characteristic curve of 0.932 and 0.914, respectively, in distinguishing bladder cancer samples from non-tumor controls. Genes such as PRAC1 and PCDH11Y were identified as high-impact predictors related to sex hormones or chromosomes for male tumor development. In the female-specific panel, genes related to aberrant androgen signaling across tumor types like AR, PLXNA1, USP54, and PMEPA1 were influential. These results offer potential targets for further in vivo/vitro experimentation and provide a framework for constructing high-performance gene panels related to sex-specific bladder cancer biology

How Policing Data Visualizations Affect Comprehension, Decision Confidence, and Perceptions of Racial Disparities

Police departments use public dashboards to share use-of-force data for policymaking and public awareness, but it remains unclear how visualization formats affect how people interpret this information. This between-subjects study with 64 participants compares absolute use-of-force incident counts (Totals) and population-adjusted rates (Rates) across four United States cities. The research included a quantitative analysis of graph comprehension, policy prioritization, confidence ratings, and attitude change, as well as a qualitative examination of open-ended responses. Results showed a strong framing effect: those who viewed absolute numbers prioritized Aurora, Colorado (highest incidents) for policy intervention, often disregarding population baselines, while those viewing per-capita rates prioritized Burlington, Vermont (highest rate). Despite high visual literacy, participants made confident policy recommendations while admitting insufficient data. Both groups requested race-specific incident breakdowns, which were missing. Findings suggest effective police transparency requires integrated presentations of absolute numbers, per-capita rates, and race-specific data to support valid policy decisions