Search Results (235)

Black gay and bisexual older men face numerous barriers across the life course that can contribute to negative health and well-being as they age. Drawing on strengths-based social determinants discussed in the health literature and literature on intersectionality, justice, and critical consciousness, this study examines qualitative data from seventeen Black gay and bisexual older men about sources and strategies of resilience and thriving amidst intersecting systems of power and oppression that shape health inequities. The findings revealed an evolution of positive support networks across their life courses, including biological family and families of choice such as “houses” and support groups. Early and ongoing negative experiences relating to intersecting positionalities (e.g., race, gender, sexual orientation) also provided sources of strength and resilience. Participants identified three strategies for building resilience and thriving: naming external ignorance, acknowledging common struggles, and reconciling contradictions. These strategies reflected various levels of critical consciousness that helped them navigate complex and intersecting systems of power that they encountered as Black gay men across the life course. Overall, the findings underscore the importance of considering intersecting systems of power and critical consciousness when examining resilience and social determinants of health and contribute new insights on a vastly understudied population. Full article

The demand for high-performance computing (HPC) continues to grow, driven by its critical role in advancing innovations in the rapidly evolving field of artificial intelligence. HPC has now entered the era of exascale supercomputers, introducing significant challenges related to sustainability. Balancing HPC performance with environmental sustainability presents a complex, multi-objective optimization problem. To the best of the author’s knowledge, no recent comprehensive investigation has explored the interplay between supercomputer performance and sustainability over a five-year period. This paper addresses this gap by examining the balance between these two aspects over a five-year period. This study collects and analyzes multi-year data on supercomputer performance and energy efficiency. The findings indicate that supercomputers pursuing higher performance often face challenges in maintaining top sustainability, while those focusing on sustainability tend to face challenges in achieving top performance. The analysis reveals that both the performance and power consumption of supercomputers have been rapidly increasing over the last five years. The findings also reveal that the performance of the most computationally powerful supercomputers is directly proportional to power consumption. The energy efficiency gains achieved by some top-performing supercomputers become challenging to maintain in the pursuit of higher performance. The findings of this study highlight the ongoing race toward zettascale supercomputers. This study can provide policymakers, researchers, and technologists with foundational evidence for rethinking supercomputing in the era of artificial intelligence. Full article

Background/Objectives: People are better at recognizing the faces of racial in-group members than out-group members. This own-race bias relies on pattern recognition and memory processes, which rely on hemispheric specialization. We hypothesized that handedness, a proxy for hemispheric specialization, would moderate own-race bias. Specifically, consistently handed individuals perform better on tasks that require the hemispheres to work independently, while inconsistently handed individuals perform better on tasks that require integration. This led to the hypothesis that inconsistently handed individuals would show less own-race bias, driven by an increase in accuracy. Methods: 281 participants completed the study in exchange for course credit. Of those, the sample was isolated to Caucasian (174) and African American individuals (41). Participants were shown two target faces (one Caucasian and one African American), given several distractor tasks, and then asked to identify the target faces during two sequential line-ups, each terminating when participants made an identification judgment. Results: Continuous handedness score and the match between participant race and target face race were entered into a binary logistic regression predicting correct/incorrect identifications. The overall model was statistically significant, Χ² (3, N = 430) = 11.036, p = 0.012, Nagelkerke R² = 0.038, culminating in 76% correct classifications. Analyses of the parameter estimates showed that the racial match, b = 0.53, SE = 0.23, Wald Χ² (1) = 5.217, p = 0.022, OR = 1.703 and the interaction between handedness and the racial match, b = 0.51, SE = 0.23, Wald test = 4.813, p = 0.028, OR = 1.671 significantly contributed to the model. The model indicated that the probability of identification was similar for own- or cross-race targets amongst inconsistently handed individuals. Consistently handed individuals, by contrast, showed an increase in accuracy for the own-race target and a decrease in accuracy for cross-race targets. Conclusions: Results partially supported the hypotheses. Inconsistently handed individuals did show less own-race bias. This finding, however, seemed to be driven by differences in accuracy amongst consistently handed individuals rather than a hypothesized increase in accuracy amongst inconsistently handed individuals. Underlying hemispheric specialization, as measured by proxy with handedness, may impact the own-race bias in facial recognition. Future research is required to investigate the mechanisms, however, as the directional differences were different than hypothesized. Full article

The design and optimization of drive distribution strategies are critical for enhancing the performance of Formula Student electric racing cars, which face demanding operational conditions such as rapid acceleration, tight cornering, and variable track surfaces. Given the increasing complexity of racing environments and the need for adaptive control solutions, a multi-mode adaptive drive distribution strategy for four-wheel-drive Formula Student electric racing cars is proposed in this study to meet specialized operational demands. Based on the dynamic characteristics of standardized test scenarios (e.g., straight-line acceleration and figure-eight loop), two control modes are designed: slip-ratio-based anti-slip control for longitudinal dynamics and direct yaw moment control for lateral stability. A CarSim–Simulink co-simulation platform is established, with test scenarios conforming to competition standards, including variable road adhesion coefficients (μ is 0.3–0.9) and composite curves. Simulation results indicate that, compared to conventional PID control, the proposed strategy reduces the peak slip ratio to the optimal range of 18% during acceleration and enhances lateral stability in the figure-eight loop, maintaining the sideslip angle around −0.3°. These findings demonstrate the potential for significant improvements in both performance and safety, offering a scalable framework for future developments in racing vehicle control systems. Full article

Access to traditional financial institutions plays a key role in enhancing positive financial outcomes. However, some consumers within the United States experience discrimination from these same institutions. In particular, discrimination based on race and gender has historically been tied to outcomes such as lower service quality and a lack of access to credit. While the previous literature has discussed some of the discriminatory practices that these groups have faced, there is a lack of research on how these groups respond to discrimination from financial institutions. Through a series of logistic regressions, the authors analyzed how race, ethnicity, and gender are related to reporting experiences of discrimination. The authors then explored how consumers react to discrimination by looking at five reported reactions. Primary results show that Black consumers were more likely than most other racial groups to experience financial discrimination. Additionally, women were less likely than men to report financial discrimination. Race was shown to be a significant factor in four of the five reactions to discrimination, while gender was a factor in two of the reactions. The findings further show that after experiencing financial discrimination, most individuals turned to non-traditional financial services as a direct result of the bias or racism. Full article

Health literacy is a critical determinant of health outcomes, yet it is often overlooked, particularly among marginalized groups. This paper explores the significance of health literacy, with a particular focus on low-income African American and Black (AA/B) men, a population that faces unique challenges due to intersecting factors such as race, gender, socioeconomic status, and educational disparities. We examine how these factors contribute to health literacy gaps, highlighting adverse effects on health outcomes for AA/B men compared to the general population. Additionally, we stress the growing importance of digital literacy in an increasingly technology-driven world. Not actively addressing digital health literacy, especially within chronic disease self-management programs (CDSMPs), further exacerbates health disparities within this group. Recommendations are provided for improving health literacy, with specific strategies to also enhance general literacy and digital literacy, among low-income AA/B men. The paper also advocates for a systematic review of the existing literature on health literacy among this group, emphasizing the need for tailored interventions that account for the unique challenges faced by low-income AA/B men. In conclusion, the paper underscores the critical need for targeted research and practical approaches to improve health literacy and ultimately health outcomes for AA/B men in the digital age, particularly through CDSMPs. Full article

This study examines how U.S. immigration policies enact legal violence and multigenerational punishment through the spousal reunification process, particularly in mixed-status, transnational families. Building on the concept of “deportability,” we introduce “importability” to describe a beneficiary’s potential to secure permanent residency, which varies according to social markers such as race, gender, and region of origin. Drawing from a content analysis of threads on the Immigration Pathways (IP) web forum, we analyze discussions among U.S. citizen petitioners navigating marriage-based green card applications, with a focus on experiences involving administrative processing (AP) (i.e., marriage fraud investigations). Our findings show that couples who do not align with the state’s conception of “proper” family—particularly U.S. citizen women petitioning for Black African partners—face intensified scrutiny, long delays, and burdensome requirements, including DNA tests and surveillance. These bureaucratic obstacles produce prolonged family separation, financial strain, and diminished sense of belonging, especially for children in single-parent households. Through the lens of “importability,” we reveal how legal violence and multigenerational punishment of immigration policies on mixed-status families beyond deportation threats, functioning as a gatekeeping mechanism that disproportionately affects marginalized families. This research highlights the understudied consequences of immigration policies on citizen petitioners and contributes to a broader understanding of inequality in U.S. immigration enforcement. Full article

Background/Objectives: Sports tourism, particularly international running events such as half marathons and marathons, has rapidly grown due to rising health consciousness and active lifestyles. Runners competing abroad face unique nutritional challenges that extend beyond physiological needs, including adaptation to local food cultures and psychosocial factors. This study aims to explore the nutritional difficulties encountered by international runners during competitions abroad, using participants of the Poznan Half Marathon 2025 as a case example. Methods: A qualitative research design was employed, involving semi-structured in-depth interviews with 12 international runners from the United Kingdom, Germany, and Ukraine. Participants had at least two years of experience competing internationally. Results: Four primary categories of nutritional challenges emerged: (1) quality and availability of food, (2) adaptation to local eating habits and physiological impacts, (3) hydration and access to appropriate fluids, and (4) logistical factors and the interactions between psychological stress, physical well-being, and nutritional choices. These factors influenced runners’ preparation, race-day performance, and recovery, highlighting the complexity of managing nutrition in unfamiliar environments. Conclusions: Nutritional challenges for international runners are multidimensional, requiring flexible and culturally sensitive nutritional strategies. Although these findings offer useful insights, they are based on a small, specific sample and should be generalized with caution. Further research is necessary to explore the broader applicability of the findings and their relevance to diverse athletic populations and contexts. Full article

Despite advances in cancer care, disparities persist. The collection of the social determinants of health (SDOH) is fundamental to addressing disparities. However, SDOH are inconsistently collected in many regions of the world. This two-phase multiple methods study examined patient and community perspectives regarding SDOH data collection in Canada. In phase 1, a survey was administered to patients at a cancer centre (n = 549) to assess perspectives on an SDOH data collection tool. In phase 2, broader perspectives were sought through a community consultation with patient partners experiencing structural inequality (n = 15). Most participants were comfortable with SDOH data collection. Of survey respondents, 95% were comfortable with the collection of language, birthplace, sex, gender, education, and disability, and 82% to 94% were comfortable with SES, sexual orientation, social support, and race/ethnicity. Discomfort levels did not differ across subgroups, except women were more uncomfortable disclosing SES (OR: 2.00; 95%CI: 1.26, 3.19). Most (71%) preferred face-to-face data collection with a healthcare professional and only half were comfortable with storage of SDOH in electronic health records. Open-ended survey responses (n = 1533) and the community consultation revealed concerns about privacy, discrimination, relevance to care, and data accuracy. SDOH data collection efforts should include a clear rationale for patients, training for providers, strong data privacy and security measures, and actionable strategies to address needs. Full article

Background: Teen dating violence (TDV) is a serious public health concern, with sexual and gender minority youth (SGMY) at elevated risk due to minority stress and systemic inequalities. This systematic review examines individual, relational, and contextual risk factors for TDV among SGMY. Methods: A systematic search was conducted in Scopus, Web of Science, and APA PsycInfo on 10 December 2024. Studies published between 2014 and 2024 focusing on teen dating violence (TDV) as an outcome among sexual and gender minority youth (SGMY) aged 13–19 were included. Study selection was independently performed by multiple reviewers using Rayyan. Risk of bias was assessed using the JBI Critical Appraisal Tools. Due to heterogeneity in the study design and measurement tools, a narrative synthesis was conducted. Results: Six risk domains emerged: (1) Demographic/Identity (e.g., gender, orientation, or race); (2) Psychological/Behavioral (e.g., distress or substance use); (3) Violence/Bullying (e.g., cyberbullying or exclusion); (4) Family/Sexual Abuse (e.g., family rejection); (5) Relational/Social (e.g., partner outing); and (6) School/Community (e.g., non-inclusive environments). Bisexual, pansexual, transgender, and racialized youth showed heightened vulnerability. Most studies were conducted in the USA and relied on non-validated TDV measures and cross-sectional designs, limiting comparability and causal inference. Conclusions: SGMY face unique, often overlooked TDV risks. There is a need for intersectional, longitudinal research and inclusive, developmentally appropriate prevention efforts that address both relational and structural factors. This review received no external funding and was not registered. Full article

Background: Cholangiocarcinoma, malignancies arising from the intrahepatic and extrahepatic bile ducts, has increased in incidence in the United States over the past few decades. The reported incidence of cholangiocarcinomas is high, particularly in specific racial groups such as Asian and Pacific Islander patients. Race also significantly impacts disparities in healthcare utilization and clinical outcomes. Our study focused on the impact of race on admission, clinical outcomes, and disposition of cholangiocarcinoma. Methods: We performed a retrospective analysis of cholangiocarcinoma-related hospital admissions, using the National Inpatient Sample for the year 2022. Patients were stratified according to race into the following groups: White, African American, Hispanic, Asian or Pacific Islander, Native American, and Other. The data analysis was performed using STATA/BE version 18.5. Univariable and multivariable logistic regression models were applied to evaluate the relationship between race and clinical and healthcare utilization outcomes. Results: In 2022, 7479 hospitalizations were recorded for cholangiocarcinoma in the United States. Among these, 65.99% were White, 13.27% Hispanic, and 10.13% African American. There was a statistically significant difference in gender distribution across racial groups (p < 0.001), with males comprising the majority in all groups. Males outnumbered females in all racial groups except among the Hispanic group. Significant racial disparities in mortality were observed, with White patients showing a mortality rate of 6.69%, compared to higher rates among African American (9.76%), Native American (8.51%), and Asian or Pacific Islander (8.09%) patients, while Hispanic (5.04%) and Other (5.88%) groups had lower rates (p < 0.001). Conclusions: The study underscores the racial disparities among cholangiocarcinoma hospitalizations, with African American, Native American, and Asian patients facing disproportionately higher mortality and poorer in-hospital outcomes compared to White patients. This analysis highlights the healthcare strategies and policy reforms to promote equitable treatment by mitigating these disparities and to improve cholangiocarcinoma outcomes. Full article

Traditional systems in real life lack transparency and ease of use due to their reliance on centralization and large infrastructure. Furthermore, many sectors that rely on information technology face major challenges related to data integrity, trust, and counterfeiting, limiting scalability and acceptance in the community. With the decentralization and digitization of energy transactions in smart grids, security, integrity, and fraud prevention concerns have increased. The main problem addressed in this study is the lack of a secure, tamper-resistant, and decentralized mechanism to facilitate direct consumer-to-prosumer energy transactions. Thus, this is a major challenge in the smart grid. In the blockchain, current consensus algorithms may limit the scalability of smart grids, especially when depending on popular algorithms such as Proof of Work, due to their high energy consumption, which is incompatible with the characteristics of the smart grid. Meanwhile, Proof of Stake algorithms rely on energy or cryptocurrency stake ownership, which may make the smart grid environment in blockchain technology vulnerable to control by the many owning nodes, which is incompatible with the purpose and objective of this study. This study addresses these issues by proposing and implementing a hybrid framework that combines the features of private and public blockchains across three integrated layers: user interface, application, and blockchain. A key contribution of the system is the design of a novel consensus algorithm, Proof of Energy, which selects validators based on node roles and randomized assignment, rather than computational power or stake ownership. This makes it more suitable for smart grid environments. The entire framework was developed without relying on existing decentralized platforms such as Ethereum. The system was evaluated through comprehensive experiments on performance and security. Performance results show a throughput of up to 60.86 transactions per second and an average latency of 3.40 s under a load of 10,000 transactions. Security validation confirmed resistance against digital signature forgery, invalid smart contracts, race conditions, and double-spending attacks. Despite the promising performance, several limitations remain. The current system was developed and tested on a single machine as a simulation-based study using transaction logs without integration of real smart meters or actual energy tokenization in real-time scenarios. In future work, we will focus on integrating real-time smart meters and implementing full energy tokenization to achieve a complete and autonomous smart grid platform. Overall, the proposed system significantly enhances data integrity, trust, and resistance to counterfeiting in smart grids. Full article

Health disparities among marginalized populations persist in many developed countries despite substantial population health advancements, highlighting persistent systemic inequities. Visible minorities, defined as the non-White and non-Indigenous racialized population in Canada, face earlier disease onset, worse outcomes, barriers to care, and shorter life expectancy. Conventional single-axis research frameworks, which examine factors like race, gender, or socioeconomic status in isolation, often fail to capture the complex realities of these disparities. Intersectionality theory, rooted in Black feminist thought and Critical Race Theory, offers a crucial lens for understanding how multiple systems of oppression intersect to shape health outcomes. However, its application in health research remains inconsistent, with often inadequate and tokenistic applications of this theory attributable to the limitations of a research approaches and resources, as well as biases from researchers. Integrating intersectionality with other relevant frameworks and theories in population health, such as ecosocial theory that explains how social inequalities become biologically embodied to create health inequities, strengthens the capacity to analyze health inequities comprehensively. This article advocates for thoughtful application of intersectionality in research to understand health disparities among visible minorities, urging methodological rigor, contextual awareness, and a focus on actionable interventions. By critically embedding intersectional principles into study design, researchers can move beyond describing disparities to identifying meaningful, equity-driven solutions. This approach supports a deeper, more accurate understanding of health inequities and fosters pathways toward transformative change in public health systems. Full article

Introduction: Early-onset colorectal cancer (EOCRC) is rising rapidly, particularly among the Hispanic/Latino (H/L) populations, who face disproportionately poor outcomes. The transforming growth factor-beta (TGF-β) signaling pathway plays a critical role in colorectal cancer (CRC) progression by mediating epithelial-to-mesenchymal transition (EMT), immune evasion, and metastasis. However, integrative analyses linking TGF-β alterations to clinical features remain limited—particularly for diverse populations—hindering translational research and the development of precision therapies. To address this gap, we developed AI-HOPE-TGFbeta (Artificial Intelligence agent for High-Optimization and Precision Medicine focused on TGF-β), the first conversational artificial intelligence (AI) agent designed to explore TGF-β dysregulation in CRC by integrating harmonized clinical and genomic data via natural language queries. Methods: AI-HOPE-TGFbeta utilizes a large language model (LLM), Large Language Model Meta AI 3 (LLaMA 3), a natural language-to-code interpreter, and a bioinformatics backend to automate statistical workflows. Tailored for TGF-β pathway analysis, the platform enables real-time cohort stratification and hypothesis testing using harmonized datasets from the cBio Cancer Genomics Portal (cBioPortal). It supports mutation frequency comparisons, odds ratio testing, Kaplan–Meier survival analysis, and subgroup evaluations across race/ethnicity, microsatellite instability (MSI) status, tumor stage, treatment exposure, and age. The platform was validated by replicating findings on the SMAD4, TGFBR2, and BMPR1A mutations in EOCRC. Exploratory queries were conducted to examine novel associations with clinical outcomes in H/L populations. Results: AI-HOPE-TGFbeta successfully recapitulated established associations, including worse survival in SMAD4-mutant EOCRC patients treated with FOLFOX (fluorouracil, leucovorin and oxaliplatin) (p = 0.0001) and better outcomes in early-stage TGFBR2-mutated CRC patients (p = 0.00001). It revealed potential population-specific enrichment of BMPR1A mutations in H/L patients (OR = 2.63; p = 0.052) and uncovered MSI-specific survival benefits among SMAD4-mutated patients (p = 0.00001). Exploratory analysis showed better outcomes in SMAD2-mutant primary tumors vs. metastatic cases (p = 0.0010) and confirmed the feasibility of disaggregated ethnicity-based queries for TGFBR1 mutations, despite small sample sizes. These findings underscore the platform’s capacity to detect both known and emerging clinical–genomic patterns in CRC. Conclusions: AI-HOPE-TGFbeta introduces a new paradigm in cancer bioinformatics by enabling natural language-driven, real-time integration of genomic and clinical data specific to TGF-β pathway alterations in CRC. The platform democratizes complex analyses, supports disparity-focused investigation, and reveals clinically actionable insights in underserved populations, such as H/L EOCRC patients. As a first-of-its-kind system studying TGF-β, AI-HOPE-TGFbeta holds strong promise for advancing equitable precision oncology and accelerating translational discovery in the CRC TGF-β pathway. Full article

Healthcare disparities in cancer care remain pervasive, driven by intersecting socioeconomic, racial, and insurance-related inequities. These disparities manifest in various forms such as limited access to medical resources, underrepresentation in clinical trials, and worse cancer outcomes for marginalized groups, including low-income individuals, racial minorities, and those with inadequate insurance coverage, who face significant barriers in accessing comprehensive cancer care. This manuscript explores the multifaceted nature of these disparities, examining the roles of socioeconomic status, race, ethnicity, and insurance status in influencing cancer care access and outcomes. Historical and contemporary data highlight that minority racial status correlates with reduced clinical trial participation and increased cancer-related mortality. Barriers such as insurance coverage, health literacy, and language further hinder access to cancer treatments. Addressing these disparities requires a systemic approach that includes regulatory reforms, policy changes, educational initiatives, and innovative trial and treatment designs. This manuscript emphasizes the need for comprehensive interventions targeting biomedicine, socio-demographics, and social characteristics to mitigate these inequities. By understanding the underlying causes and implementing targeted strategies, we can work towards a more equitable healthcare system. This involves improving access to high-quality care, increasing participation in research, and addressing social determinants of health. This manuscript concludes with policy recommendations and future directions to achieve health equity in cancer care, ensuring optimal outcomes for all patients. Full article