Asian Journal of Advanced Research and Reports
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A Rare Case of Life-Threatening Severe Haematuria in a Young Female Due to Angiosarcoma of the Bladder
No full textBackground: Angiosarcoma of the bladder is a rare and aggressive malignancy arising from malignant endothelium accounting for less than 2% of all sarcomas. It typically affects older adults, with few cases reported in younger individuals. The rarity and nonspecific clinical presentation make diagnosis and management particularly challenging.
Case Presentation: We report the case of a 32-year-old female who presented with life-threatening haematuria and anaemia. Initial assessment suggested bladder clots, and diagnostic cystoscopy was inconclusive due to persistent bleeding and extensive clot formation. The patient underwent emergency laparotomy, during which a biopsy from the thickened bladder wall revealed angiosarcoma though, immunohistochemistry was not available creating a diagnostic limitation. Despite aggressive resuscitation, and internal iliac artery ligation, bleeding persisted. Once stabilised, the patient underwent an open radical cystectomy with ileal conduit diversion. Postoperative recovery was initially uneventful, but the patient later succumbed to complications from anaemia and multi-organ failure within three months of diagnosis.
Discussion: This case highlights the aggressive course of bladder angiosarcoma and underscores the importance of early recognition and intervention. Due to its rarity, especially in young females without known risk factors, diagnosis is often delayed. Histopathological and immunohistochemical evaluation remain crucial for definitive diagnosis. Management requires a multimodal approach, often including radical surgery, and possibly chemotherapy or radiotherapy depending on the disease stage. Despite timely intervention, prognosis remains poor with high mortality.
Conclusion: Bladder angiosarcoma, although rare, should be considered in the differential diagnosis of unexplained haematuria, even in young patients. Prompt diagnosis and radical treatment are vital, although the prognosis remains guarded
Integrating Machine Learning and Subsurface Characterization for Improved Urban Flood Modelling and Parameter Optimization
No full textFlooding is one of the worst natural disasters which endangers lives and hampers economic activities across the globe. Construction and calibration of physical models which includes computational resources and data are the primary components of urban flood modeling. In this research, a paradigm shift is proposed by combining subsurface data with ML methodologies which advance urban flood modeling techniques as well as parameter tuning. Model accuracy and robustness are achieved through parametric value enhancement. The findings obtained shed light on the potential improvements that were observed in urban flood modeling. Such changes will facilitate better management in the contexts of urban infrastructure development, risk assessment, and hydrological resource optimization. The strategic evaluation optimization technique relies on the K-means ANN driven Genetic Algorithm when dealing with urban inundation parameters. This technique identifies sensitive parameter values while also providing optimal results to enhance model effectiveness. Subsequently, the designed inundation model underwent validation through simulating real-world rainfall data followed by an evaluative approach to test the accuracy of the proposed predictive methodology
Open Grazing and Agricultural Decline in the Sahel, Africa: Economic Costs, Legal Challenges and Environmental Impacts
No full textOpen grazing remains one of the most contentious land-use practices in the Sahel region, contributing to widespread agricultural, economic, and environmental instability. This manuscript investigates the economic effects of open grazing by synthesizing cross-disciplinary evidence from policy reports, empirical research, and legal documents. The study utilizes qualitative analysis through literature review and identifies key impact areas including crop destruction, reduced agricultural investment, household income loss, ecological degradation, and governance failures. It reveals that grazing-induced land conflicts and crop damage result in significant economic losses, with cascading effects on food security, labor productivity, and rural livelihoods. Furthermore, the research uncovers how weak enforcement of anti-grazing laws and absence of alternative pastoral systems hinder effective reform. Ecological assessments demonstrate that overgrazing leads to biodiversity loss, erosion, and declining soil fertility, worsening the region’s vulnerability to climate change. Legal analysis shows fragmented policies and resistance from national elites undermine local regulatory efforts. In response, the manuscript proposes multi-dimensional reform strategies including rotational grazing systems, land tenure security, legal harmonization, and inclusive conflict resolution frameworks. Through this holistic analysis, the study underscores the urgent need for policy integration and sustainable land management to address the intersecting economic, social, and environmental crises exacerbated by open grazing in the Sahel
Evidence-based Practice Competencies among Chinese Internship Nursing Students in Shandong Province of China: A Cross-sectional Design Study
No full textBackground: Evidence-Based Practice is a scientifically advanced nursing philosophy. At present, the main factors hindering the development of evidence-based nursing are lacking of theoretical knowledge and skills of evidence-based nursing among nursing staff. Nursing students are the main force of nursing career and participants in Evidence-Based Practice in the future, and their Evidence-Based Practice competencies affects the development of Evidence-Based Practice in China to a certain extent.
Aims: The aim of the present study is to examine the level of Evidence-Based Practice evaluation competency and analysis of influencing factors among Chinese internship nursing students in Shandong province of China.
Research Design: A quantitative study based on cross-sectional design was conducted during 2025. Total 130 undergraduate internship nursing students were selected using the Random sampling method.
Results: Total Evidence -based Practice Evaluation Competencies Questionnaires score for 130 undergraduate intern nursing students is 82.89±14.75; of which the Evidence-Based Practice attitude score was 41.83±6.58, the Evidence-Based Practice skill score was 20.53±4.70, and the Evidence-Based Practice knowledge score was 20.53±4.71;There were significant differences(p<0.05) in age ,internship hospital grade, internship duration, educated in Evidence-Based Practice practice taken a literature search course and taken Nursing research course.
Conclusion: The competency of Chinese undergraduate nursing interns in Evidence-Based Practice stands at a moderate level, reflecting both promise and opportunity. While their attitudes toward evidence-based competencies are largely positive, there remains a substantial need for enhancement in their skills and knowledge
SIR, SIRS, and SEIRS Models for Pertussis Cases in Eastern Visayas
No full textThis study analyzed the effectiveness of the Susceptible-Infected-Recovered (SIR), Susceptible-Infected-Recovered-Susceptible (SIRS), and Susceptible-Exposed-Infected-Recovered-Susceptible (SEIRS) models in predicting pertussis incidence in Eastern Visayas, Philippines. The research aimed to compare the accuracy of these models using real-world data on weekly pertussis cases for the year 2024. The study utilized a mathematical modeling approach, employing differential equations to simulate disease transmission dynamics. Baseline parameter values for each model were obtained from existing literature, and these parameters were later refined through estimation techniques, specifically by using least squares optimization to fit the models to the observed data. The models were implemented using MS Excel, and their performance was evaluated using the Root Mean Square Error (RMSE) metric. The results of the study showed that the SIR model, with final estimated parameters β = 13.5968 and γ = 13.5496, provided the most accurate prediction of pertussis incidence the region, with the lowest RMSE of 9.07. In contrast, the SIRS and SEIRS models, while incorporating more complex disease dynamics such as waning immunity and an exposed period, exhibited higher RMSE values of 12.69 and 12.74, respectively, indicating less accurate predictions. These findings suggest that traditional models like SIR may be more practical for short-term pertussis forecasting in the context of Eastern Visayas in 2024. This study also highlighted the importance of model calibration and validation using local real-world data.  
Rural Collective Economy Policy in China: A Systematic Review and Bibliometric Analysis of Trends, Themes, and Operating Mechanisms Using R Studio
No full textChina\u27s new rural collective economy policy has gained attention over the past two decades for its crucial role in rural revitalisation and sustainable development. However, the practical mechanisms for its implementation have not been thoroughly assessed and well-documented in the literature. Research synthesizing knowledge on the operational mechanisms of this policy is still inadequate. This paper addresses these gaps by conducting a systematic bibliometric analysis of 150 articles from the Web of Science database, using R software to evaluate scientific productivity and operational mechanisms related to China’s new rural collective economy. The results from the bibliometric analysis reveal a significant increase in research productivity, demonstrating high interest in the research field. The results further outline that thematic areas, such as ‘rural collective actions’, ‘collective land shareholdings’, ‘agriculture cooperatives\u27, and social capital, have progressively become research hotspots and critical operating development path mechanisms of the new rural collective economy and sustainable development in China. The new rural collective economy strengthens social networks and participation in community projects, as well as public goods and services within the village collectives. The governance structure bolsters the democratic systems of governing in the market economy. The fairness and transparency in the governing systems of the new rural collective economic structures save time, cost, and labour in the land transaction processes and collective assets. This review highlights the potential of China\u27s new rural collective economy policy to promote sustainable rural development and rural self-governance. It indicates a shift in China’s rural governance, away from direct intervention towards support for local collective actions
Exploring the Role of a Principal to Influence the School Culture, Teacher Performance and Community: A Case Study of Bhutanese School
No full textThe role of an individual is vital in a group or organization as their actions influence group’s direction and culture. This study employed a mixed method approach with surveys and open ended questions to explore the role of a principal in influencing the school culture, teacher performance, and community. The study was conducted in one of the schools in Bhutan. The findings revealed a major gap between the principal’s self-rating and the ratings of the ten teacher participants. It was found that the creation of supportive school climate, maintaining of strong community relationships and uplifting of teachers’ performance are negatively impacted due to disparity between the leader and the subordinates. Though, qualitative feedback highlighted the principal’s strengths in collaboration, it was identified areas for improvement in decision-making and empowering staff. Thus, this study concludes that a leader’s effectiveness is not only based on their actions but also on their ability to bridge the gap between their self-perception and their staff’s reality
Library and Information Science Profession in Emerging Economies: Quality, Capacity Building Measures and Challenges
No full textThis paper is concerned with the quality, capacity building measures and challenges of LIS profession in emerging economies like Nigeria. Its main thrust is to explore the present status of LIS profession in Nigeria, examine some of the critical and core skills, quality, capacity and challenges and to profess solutions. How the skills can be acquired and improve on competences, capacity building measures and ameliorate the challenges in other to effectively serve their clientele. As an exploratory research, this paper recommends that curriculum changes, use of digital technologies, proficiency in manipulating computer applications are all needed for LIS profession in emerging economies to succeed and meet the challenges of the 21st century information-based society
Cystic Hygroma in Early Pregnancy with Spontaneous Miscarriage: A Case Report
No full textAims: To report a rare case of first-trimester cystic hygroma and emphasize its diagnostic and prognostic implications.
Case Presentation: A 42-year-old nulliparous woman with a history of miscarriage and first-degree consanguinity was admitted at 10 weeks of gestation for vaginal bleeding and lower abdominal pain. Ultrasound examination revealed a missed miscarriage associated with a multiloculated cervical/nuchal cystic hygroma. The pregnancy ended in spontaneous miscarriage within hours of admission. Genetic testing was declined.
Conclusion: First-trimester cystic hygroma is a rare anomaly with a poor prognosis, frequently associated with chromosomal aneuploidy and structural malformations. Early ultrasound detection and genetic evaluation are essential for accurate diagnosis, appropriate counseling, and guiding parental decisions, particularly in resource-limited settings
Information Governance Framework for AI-Generated Synthetic Patient Data in Healthcare Research: Balancing Utility, Privacy and Algorithmic Bias Mitigation
No full textThis study develops and validates an information governance framework for AI-generated synthetic patient data in healthcare research, balancing data utility, privacy, and algorithmic bias mitigation. The introduction positions the framework as a response to stringent privacy regulations and data scarcity, integrating dynamic consent, differential privacy, and fairness-aware synthetic data generation. The literature review synthesizes theoretical foundations and identifies gaps in standardized validation and integrated governance. The methodology employs a design science approach, utilizing public datasets such as MIMIC-III, advanced generative models (GANs, VAEs, diffusion models), and blockchain-based consent systems. Validation metrics assess fidelity, utility, and bias reduction. Findings demonstrate substantial improvements in consent efficiency, data utility, and demographic fairness, though challenges persist regarding interface complexity and scalability. The conclusion affirms enhanced patient control, privacy, and equity, recommending adaptive interfaces, federated learning, and real-world pilots. The framework offers a scalable, policy-aligned solution for secure and equitable healthcare AI, supporting evidence-based innovation while safeguarding patient rights