Search Results (1,692)

Adolescents and Young adults (AYAs: 15–39 years) diagnosed with cancer face unique medical and psychosocial challenges requiring specialized care. This study conducted an environmental scan of AYA-specific programming and services currently offered across Canadian tertiary care centres. Key informants from pediatric and adult cancer centres in Canada reported on program logistics, AYA specialized staff and training opportunities, and collaboration between centres, funding, and specific areas of interest for AYA care such as palliative care, fertility, fatigue, and sexual health. Surveys were completed by 13/16 (81%) pediatric sites and 19/23 (83%) adult sites. Only about half of pediatric sites (n = 8/13) and adult sites (n = 9/19) who responded reported offering any AYA-specific cancer services or programming. One third of centres without programming reported to be working on developing programming. Only 6 sites reported to offer specialized AYA training. Several barriers were reported, such as the need for collaboration among institutions and improvement of oncofertility services. Significant disparities exist regarding geographic availability of services, the range of services available, and the populations served. Findings will guide researchers, health professionals, and provincial health authorities in the development of highquality and equitable services and programs for AYAs diagnosed with cancer across Canada. Full article

Against the backdrop of the “dual carbon” strategy and digital rural development, examining the impact of farmers’ digital literacy on the adoption and efficiency of green agricultural technologies can provide micro-level evidence and actionable policy insights for advancing the green transformation of agriculture. Through a systematic literature review and thematic analysis of 52 eligible studies, this study identifies a significant triple role of digital literacy—as an enabler, a mediating mechanism, and a potential barrier—in the adoption of green agricultural technologies. While digital literacy significantly facilitates technology adoption, its positive effects are constrained by a “capacity gap” arising from limited digital skills, low literacy levels, and inadequate digital infrastructure. Technology adoption demonstrates distinct stratification: digital information and communication technologies (ICTs) exhibit high penetration but superficial utilization; green production technologies are largely limited by capital availability; and precision agriculture, intelligent systems, and blockchain applications remain primarily at the pilot or demonstration stage. Furthermore, the interaction between digital literacy and technology adoption enhances agricultural efficiency by reducing income disparities, fostering rural entrepreneurship, and improving green total factor productivity (GTFP). This review highlights the importance of targeted policies and further research to address the capacity gap, realize sustained efficiency gains, and promote digital empowerment as a pathway to sustainable agricultural transformation. Full article

With the rapid development of Massive Open Online Courses (MOOCs), high dropout rates have become a major challenge, limiting the quality of online education and the effectiveness of targeted interventions. Although existing MOOC dropout prediction methods have incorporated deep learning and attention mechanisms to improve predictive performance to some extent, they still face limitations in modeling differences in course difficulty and learning engagement, capturing multi-scale temporal learning behaviors, and controlling model complexity. To address these issues, this paper proposes a MOOC dropout prediction model that integrates multi-scale convolution with a symmetric dual-attention mechanism, termed SDA-Net. In the feature modeling stage, the model constructs a time allocation ratio matrix (MRatio), a resource utilization ratio matrix (SRatio), and a relative group-level ranking matrix (Rank) to characterize learners’ behavioral differences in terms of time investment, resource usage structure, and relative performance, thereby mitigating the impact of course difficulty and individual effort disparities on prediction outcomes. Structurally, SDA-Net extracts learning behavior features at different temporal scales through multi-scale convolution and incorporates a symmetric dual-attention mechanism composed of spatial and channel attention to adaptively focus on information highly correlated with dropout risk, enhancing feature representation while maintaining a relatively lightweight architecture. Experimental results on the KDD Cup 2015 and XuetangX public datasets demonstrate that SDA-Net achieves more competitive performance than traditional machine learning methods, mainstream deep learning models, and attention-based approaches on major evaluation metrics; in particular, it attains an accuracy of 93.7% on the KDD Cup 2015 dataset and achieves an absolute improvement of 0.2 percentage points in Accuracy and 0.4 percentage points in F1-Score on the XuetangX dataset, confirming that the proposed model effectively balances predictive performance and model complexity. Full article

Digital transformation in agriculture addresses key challenges such as climate change, water shortages, and sustainable production. Precision agriculture technologies rely on the Internet of Things (IoT) sensor networks, analytics, and automated systems to manage resources efficiently and increase productivity. Fragmented infrastructures and vendor-specific platforms lead to unintegrated data silos that obstruct regional solutions. This paper will emphasize FIWARE, an open-source, standard-based platform that can be integrated with existing agricultural sensors in municipalities or regions. FIWARE takes all these disparate sensors (soil probes, weather stations, and irrigation meters) and integrates them into a single real-time information system, providing a set of decision support tools to the user to facilitate adaptive irrigation. Case studies show the benefits of FIWARE, including water savings, reduced runoff, better decision-making, and improved climate resilience. Full article

Background/Objectives: This study seeks to evaluate the clinical characteristics of newly diagnosed male breast cancers within the traditionally underserved Bronx population at risk for poorer health outcomes. Methods: We retrospectively searched our database for male patients who presented for mammographic evaluation between 1 January 2016 and 1 October 2024. The primary outcomes were the prevalence of biopsy-proven male breast cancer and its association with gynecomastia and TNM stage at diagnosis. Clinical data, including TNM staging, receptor status, risk factors, and patient demographics, were recorded for patients with biopsy-proven breast cancer based on biopsy results. Two dedicated breast imagers retrospectively evaluated mammograms of these patients to determine by consensus the presence of gynecomastia. Analyses were descriptive in nature. Results: During the study period, 423 screening mammograms and 1775 diagnostic mammograms were performed on male patients. Twenty-six male patients with biopsy-proven breast cancer were identified (two were bilateral and four were multifocal). In total, 69% of our male breast cancer patients (18 out of 26) demonstrated gynecomastia, which was similar across demographic groups, ranging from 63 to 75%. Out of the three patients with Stage 4 disease, two were Black and one was White. Stage 3 or higher disease was seen in 29% of our Black patients, 12% of our White patients, and 0% of our Hispanic patients. Conclusions: Male breast cancer in this Bronx population was frequently associated with gynecomastia and showed notable demographic disparities. Black patients presented with more advanced disease than other demographic groups. These descriptive findings highlight areas of further investigation and may help inform future outreach and early detection efforts in high-risk, underserved communities. This retrospective, single-institution analysis was limited by a small sample size and did not include formal statistical testing; therefore, the findings are descriptive and warrant validation with larger cohorts. Full article

This study investigates the relationship between stock returns and income inequality in South Africa, a country marked by persistently high levels of income disparities and a sophisticated and structurally unique financial market. Despite the Johannesburg Stock Exchange (JSE) being one of the most developed and liquid markets in Africa, stock ownership remains limited to a small segment of the population, often reinforcing pre-existing income inequalities. This study determines the relationship between stock returns and income distribution using the ARDL bound test methodology. Using time series data from 1975 to 2024, the study examines the extent to which stock market returns influence income distribution. The findings of the study suggest a positive relationship between stock returns and income distribution. This relationship suggests that higher stock market development disproportionately benefits capital holders. The long-term relationship seems to have limited feedback from inequality to stock returns. The findings aim to inform policies on inclusive financial participation and broad-based wealth generation to address South Africa’s structural inequalities. Full article

Hydrogen has emerged as a cornerstone of global decarbonisation strategies, offering a flexible pathway to reduce dependence on fossil fuels and accelerate progress towards net-zero targets. However, the development of a globally integrated hydrogen economy remains uneven, reflecting disparities in renewable energy potential, infrastructure readiness, investment capacity, and policy commitment. To better understand these differences and the barriers they create, this study undertakes a comprehensive comparative assessment of the global hydrogen supply chain encompassing resources, production, storage, transport, and end-use applications. Further, a structured analytical framework comprising ten principles and twenty-nine sub-factors was developed to evaluate national hydrogen policies, technological readiness, and enabling conditions across twenty-six countries. The results show that the United States, China, Japan, South Korea, and Germany lead global progress, while many countries remain at an early stage of engagement. These findings further inform persistent regional asymmetries and emphasise the need for stronger international coordination. Drawing on these findings, the paper advances targeted policy and research recommendations to lower production costs, expand storage and transport capacity, and harmonise regulatory frameworks, thereby defining a coherent pathway towards a secure, cost-competitive, and equitable global hydrogen economy by 2050. Full article

The Indonesian government has collected bridge inspection data since 2019. This data reveals the deterioration trend of existing bridges. These findings help to evaluate the current deterioration curve and can inform more efficient inspection and maintenance methods, which have not been updated since 1993. The first purpose is to evaluate the current deterioration of the Bridge Management System (BMS) model by comparing it with a trend developed from existing conditions. A secondary objective is to compare deterioration trends derived from Indonesian inspection data using the BMS with those from Florida using NBIS. The deterioration trend is found by correlating soundness and bridge age. This study shows that none of the inspection-based trends align with the typical BMS deterioration curve. The real deterioration trends are faster. Many factors influence the trendline, such as bridge type, construction material, and length. There is a clear disparity in the deterioration trends of the superstructure, deck, waterway/embankment, and substructure based on inspection data from Indonesian bridges. The superstructure deteriorates faster and more quickly than the deck, even though both are in the same section. The waterway/embankment deteriorates faster than the deck. The bridges deteriorate faster in the first 10 years. In contrast, consistent deterioration trends across all components are found in Florida bridges. In Florida, bridge components deteriorate at a rate of 0.0447 to 0.056 per year in condition score during the first 20 years. After this period, the deterioration rate declines, as indicated by a reduced slope in the trend line. Ultimately, this study directly compares trends in bridge deterioration between Indonesia and Florida using large-scale inspection data. The results evaluate Indonesia’s Bridge Management System empirically and reveal how different inspection and maintenance practices affect bridge deterioration. Full article

Background and Clinical Significance: Malaria remains a significant public health issue in Latin America, where Plasmodium vivax predominates but P. falciparum continues to circulate. Mixed-species infections are uncommon and can pose diagnostic challenges, particularly when parasite densities differ markedly, increasing the risk of underdetecting P. falciparum with conventional methods. Case report: We report a 9-year-old boy from an endemic area with a six-day febrile syndrome. Thick smear and peripheral blood film microscopy, complemented by rapid diagnostic tests for pan-Plasmodium and HRP2 antigens, confirmed a mixed infection with P. vivax (5500 parasites/µL) and P. falciparum (562 parasites/µL). The patient was hemodynamically stable, without severe malaria criteria, and laboratory values were within normal limits. Following confirmation of normal glucose-6-phosphate dehydrogenase activity, treatment with artemether–lumefantrine was initiated, followed by primaquine for hypnozoite eradication. Clinical evolution was favorable, with progressive defervescence, treatment tolerance, and documented parasite clearance. Conclusions: This case illustrates the risk of underestimating P. falciparum in mixed infections with disparate parasitemias and highlights the value of integrated diagnostic approaches in resource-limited endemic settings. It also underscores surveillance limitations that can misclassify mixed infections, potentially affecting epidemiological estimates and treatment strategies. Timely recognition and comprehensive diagnostic evaluation are essential to ensure appropriate antimalarial therapy, prevent complications, and inform public health interventions in regions where both species coexist. Full article

Background: Dementia is an increasing public health challenge in Mexico, yet recent national data on mortality patterns remain limited. This study examines temporal trends in dementia-related mortality and its sociodemographic and ecological characteristics among adults aged ≥65 years from 2017 to 2023. Methods: National mortality records from the General Directorate of Health Information were analyzed. Annual dementia-related mortality rates were calculated based on mid-year population estimates from CONAPO. Trends were assessed with regression analysis, including population offsets, and individual- and state-level characteristics were evaluated. Results: Between 2017 and 2023, dementia-related deaths increased from 761 to 1425, corresponding to an observed rise from 7.9 to 14.6 deaths per 100,000 inhabitants aged ≥65 years. Period trend indicated an average annual expected increase of 18.6% in dementia related mortality. A transient decline occurred in 2020–2021, coinciding with the COVID-19 pandemic. At the individual level, higher education was associated with greater odds of dementia certification, whereas Indigenous ethnicity appeared protective, which may reflect patterns consistent with diagnostic and reporting disparities. Higher state-level life expectancy correlated with higher dementia mortality, while greater population aging was inversely associated. Conclusions: Dementia-related mortality in Mexico shows a sustained upward trend with regional heterogeneity and apparent inequities in diagnosis and reporting. Strengthening mortality surveillance, improving certification quality, and integrating dementia indicators into national non-communicable disease registries are essential to guide equitable policy responses. Full article

Women with intellectual disabilities (IDs) face persistent health inequities, particularly in preventive services such as breast cancer screening, where participation rates remain disproportionately low. These disparities contribute to higher mortality and poorer survivorship outcomes, often linked to later-stage diagnoses. To better understand these challenges and inform the development of inclusive screening programs, this qualitative study conducted in Austria explored barriers, facilitators, and needs related to breast cancer screening from the dual perspectives of 17 women with mild-to-moderate IDs aged 45 and older and 10 caregivers. Semi-structured focus groups and interviews were analyzed thematically within a constructivist framework, integrating perspectives from both groups. Barriers included social taboos around sexuality, psychological distress, exclusion through standardized procedures, and unclear responsibility among stakeholders. Facilitators involved person-centered communication, accessible information, emotional and practical support, and familiar healthcare environments. Women with IDs expressed a strong desire for education, autonomy, and inclusion, while caregivers played a pivotal role in enabling access. These findings demonstrate that low screening participation among women with IDs is driven by systemic and organizational barriers rather than lack of health awareness or willingness to participate. Without structurally inclusive design, organized screening programs risk perpetuating preventable inequities in early detection. Embedding accessibility, clear accountability, and person-centered communication as standard features of breast cancer screening is therefore a public health priority to reduce avoidable late-stage diagnoses and narrow survival disparities for women with IDs. Full article

Understanding regional disparities in Chinese modernization is essential for achieving coordinated and sustainable development. This study develops a multi-dimensional evaluation framework, integrating grey relational analysis, entropy weighting, and TOPSIS to assess provincial modernization across China from 2018 to 2023. The framework operationalizes Chinese-style modernization through five dimensions: population quality, economic strength, social development, ecological sustainability, innovation and governance, capturing both material and institutional aspects of development. Using K-Means clustering, kernel density estimation, and convergence analysis, the study examines spatial and temporal patterns of modernization. Results reveal pronounced regional heterogeneity: eastern provinces lead in overall modernization but display internal volatility, central provinces exhibit gradual convergence, and western provinces face widening disparities. Intra-regional analysis highlights uneven development even within geographic clusters, reflecting differential access to resources, governance capacity, and innovation infrastructure. These findings are interpreted through modernization theory, linking observed patterns to governance models, regional development trajectories, and policy coordination. The proposed framework offers a rigorous, data-driven tool for monitoring modernization progress, diagnosing regional bottlenecks, and informing targeted policy interventions. This study demonstrates the methodological value of integrating grey system theory with multi-criteria decision-making and clustering analysis, providing both theoretical insights and practical guidance for advancing balanced and sustainable Chinese-style modernization. Full article

Despite a growing number of Earth Observation satellites, a critical observational gap persists for timely, high-resolution flood mapping, primarily due to infrequent satellite revisits and persistent cloud cover. To address this issue, we propose a novel framework that synergistically fuses complementary data from three public sensor types. Our methodology harmonizes these disparate data sources by using surface water fraction as a common variable and downscaling them with flood susceptibility and topography information. This allows for the integration of sub-daily observations from the Visible Infrared Imaging Radiometer Suite and the Advanced Himawari Imager with the cloud-penetrating capabilities of the Advanced Microwave Scanning Radiometer 2. We evaluated this approach on the February 2022 flood in Brisbane, Australia using an independent ground truth dataset. The framework successfully compensates for the limitations of individual sensors, enabling the consistent generation of detailed, high-resolution flood maps. The proposed method outperformed the flood extent derived from commercial high-resolution optical imagery, scoring 77% higher than the Copernicus Emergency Management Service (CEMS) map in the Critical Success Index. Furthermore, the True Positive Rate was twice as high as the CEMS map, confirming that the proposed method successfully overcame the cloud cover issue. This approach provides valuable, actionable insights into inundation dynamics, particularly when other public data sources are unavailable. Full article

Background: Prostate cancer remains a significant public health burden globally, particularly in sub-Saharan Africa, where rising incidence rates are compounded by limited screening, late-stage diagnosis and disparities in healthcare access. In South Africa, the Eastern Cape Province reports high prostate cancer prevalence, with many patients presenting at advanced stages. Understanding the epidemiological profile of affected individuals is critical for developing targeted health strategies. Objectives: This sub-study aims to describe the epidemiological characteristics of patients diagnosed with prostate cancer, using secondary data from Nelson Mandela Academic Hospital (NMAH), focusing on patients seen between March 2020 and November 2021. Methods: A quantitative cross-sectional study design is employed. De-identified secondary data extracted from clinical records of male patients diagnosed with prostate cancer and managed at NMAH during the study period. Variables include demographic information, clinical characteristics, health service utilization indicators. Analysis: Data will be captured and coded in Microsoft excel 2013 (Microsoft corporation, Seattle, WA, USA). The data will then be exported to STATA 18 for analyses. Descriptive statistics will be used to summarize the data. Inferential analyses such as logistic regression and chi-square tests will be used to explore associations between variables and treatment outcomes. The study provides insights into the demographic and clinical profiles of prostate cancer patients in a high-burden setting. It is anticipated that findings will highlight the age distribution, stage at diagnosis, and treatment patterns among patients diagnosed with prostate cancer. This will inform future prevention and intervention strategies in the Eastern Cape Province. Conclusions: By mapping out the epidemiological patterns of prostate cancer in the Eastern Cape through this sub-study, the research contributes to evidence-based planning and resource allocation, ultimately supporting efforts to reduce prostate cancer morbidity and mortality in rural South Africa. Full article

Against the backdrop of rising global carbon emissions, promoting active transportation modes such as walking and cycling has become a key strategy for countries worldwide to meet carbon reduction targets and advance the goals of sustainable development. In China, the concept of low-carbon mobility has gained rapid traction, leading to a significant increase in public demand for non-motorized travel options like walking and cycling. From the perspective of inclusive urban development, gender imbalances in sample representation during design and evaluation processes have contributed to homogenization and a lack of diversity in urban slow-traffic environments. To address this issue, this study adopts a problem-oriented approach. First, we collect street scene images of slow-traffic environments through self-conducted field surveys. Concurrently, we gather satisfaction survey responses from 511 urban residents regarding existing slow-traffic streets, identifying three key environmental evaluation indicators: safety, liveliness, and beauty. Second, an experimental analysis is conducted to compare machine-generated assessments based on self-collected street view data with manual evaluations performed by 27 female participants. The findings reveal significant perceptual differences between genders in the assessment of slow-moving environments, particularly regarding attention to environmental elements, challenges in utilizing non-motorized lanes, and overall environmental satisfaction. Moreover, notable discrepancies are observed between machine scores and manual assessments performed by women. Based on these findings, this study investigates the underlying causes of such perceptual disparities and the mechanisms influencing them. Finally, it proposes female-inclusive strategies aimed at enhancing the quality of slow-traffic environments, thereby addressing the current absence of gender considerations in their design. This research seeks to provide a robust female perspective and empirical evidence to support improvements in the quality of slow-moving environments and to inform strategic advancements in their design. The findings of this study can provide a theoretical and empirical basis for the optimization of gender-inclusive non-motorized transportation environment design, policy formulation, and subsequent interdisciplinary research. Full article