39506 research outputs found
Sort by
Spatio-temporal patterns of urban property crime in Malaysia: towards safer, inclusive cities (SDGs 11 and 16)
No full textUrban property crime impedes sustainable development, yet its spatial and temporal dynamics remain poorly understood in Malaysian cities. To address this gap, the spatial and temporal clustering of property crime across Selangor, Kuala Lumpur, and Putrajaya was analyzed for 2015–2020. Police‐reported incidents were geocoded to precinct boundaries and examined using GIS‐based spatial statistics: Global Moran’s I measured overall spatial autocorrelation and Getis–Ord Gi* identified local crime hotspots. Results show significant positive spatial autocorrelation each year (Moran’s I = 0.114–0.297; Z = 5.33–13.22; p < 0.001), indicating pronounced clustering. Hotspot analysis revealed persistent high-risk clusters: notably, the Jinjang and Tun H.S. Lee precincts of Kuala Lumpur were hotspots every year, and areas like Jalan Tun Razak had Gi* Z-scores up to ≈5.6 (p ≪ 0.01). These clusters accounted for a large share of incidents (e.g. Ampang 2018, Z ≈ 5.62), underscoring strong spatial concentration of crime. The spatial evidence supports targeted, evidence‐based policing and aligns with SDG 16 and SDG 11 by guiding strategic crime reduction for safer, more inclusive cities. These findings yield a robust GIS framework for spatially informed crime prevention and urban planning, enhancing institutional accountability and advancing sustainable city objectives
Isolation of Proteus sp. Closely Related to P. Vulgaris (Vulgaris/hauseri Complex) from Ornamental Koi (Cyprinus rubrofuscus) and its Pathogenicity
No full textKoi (Cyprinus rubrofuscus) is a world-famous ornamental fish known for its unique characteristics and economic value. This species is susceptible to various infections, leading to high mortality and morbidity rates. In this study, bacterial pathogens isolated from naturally diseased koi were identified as belonging mainly to the genera Aeromonas and Proteus through comprehensive characterisation and molecular identification. Experimental infections with Proteus sp. closely related to Proteus vulgaris (vulgaris/hauseri complex) showed some clinical signs very similar to those in naturally infected koi, suggesting that Proteus sp. in this study is a possible pathogen in addition to Aeromonas, indicating a potential co-infection. The median lethal dose (LD50) for Proteus sp. was determined to be 1.7 × 108 CFU/mL, with histopathological analysis showing changes such as fusions, lymphocyte aggregation, and necrosis in the kidney and liver. The bacterium was found to be sensitive to various antibiotics, suggesting that broad-spectrum antibiotics may be effective in treating the pathogen. This study represents the isolation of Proteus sp. closely related to P. vulgaris (vulgaris/hauseri complex) from koi and provides valuable insights for the prevention and management of related disease outbreaks. The study on bacterial infections in koi fish, particularly the isolation and characterization of Aeromonas species alongside Proteus sp., highlights significant implications for koi health management. The findings underscore the pathogenicity, potential for coinfection, and the susceptibility of Proteus sp. to broad-spectrum antibiotics, providing key understanding for disease outbreak management in ornamental koi populations
Corn Starch/Soybean Wax Double Coated Biochar‑based Controlled‑release Nitrogen Fertilizer: Water Retention, Release Kinetics and Okra Growth
No full textWater-soluble fertilizers, although widely used to enhance crop productivity, often lead to environmental pollution due to their rapid nutrient loss. To address this issue, coated biochar-based fertilizers have gained attention for improving nutrient use efficiency and reducing environmental impacts, with their performance greatly depends on the formulation of the encapsulating materials. Biopolymers such as starch offer a biodegradable alternative to synthetic polymers, while soybean wax provides an environmentally-friendly and highly hydrophobic coating capable of enhancing the controlled-release behaviour. Together, these materials present a promising strategy for developing more sustainable controlled-release fertilizer formulations. In this study, a double-layered coated biochar-based fertilizer was synthesized using corn starch as the inner coating and soybean wax as the outer layer to enhance the nutrient release performance and support sustainable agriculture. The double-coated formulation improved the water retention and slowed the nitrogen release as compared with the uncoated fertilizer, following a zero-order kinetic mechanism. These controlled-release characteristics enhanced the plant performance as evidenced by the increased okra height. Overall, the corn starch/soybean wax coating demonstrated a strong potential for reducing the nutrient loss while promoting crop growth
BLENDING RESEARCH, ARTIFICIAL INTELLIGENCE, & NEUROSCIENCE: ADVANCING INNOVATION DESIGN (BRAIN-AID)
No full textThis project presents an AI-enhanced e-learning ecosystem for the course KMF1053 Cognitive Neuroscience, developed to transform student engagement and connect theoretical concepts with real-world applications. Traditional lecture-based approaches often limit active participation and restrict opportunities for students to apply neuroscience knowledge meaningfully. To overcome these challenges, the course integrates AI-driven innovations such as Curipod for
interactive lessons with real-time feedback, Wix e-Portfolios with AI-assisted infographic design,
AI-powered video platforms (Wave.video, Flexclip, InVideo) for start-up pitching, and AI-enabled reflection analysis. The activities were closely aligned with the course learning outcomes. For CLO2, which emphasizes demonstrating the roles of the brain in relation to human behaviours, perceptions, and higher mental functions, students engaged in Curipod activities that required them to propose neuroscience-based strategies for improving attention while explaining the
underlying brain mechanisms. Curipod’s AI clustered responses and provided immediate feedback, enhancing conceptual understanding and fostering deeper engagement. This activity resulted in a 98.67% achievement of CLO2. For CLO3, which focuses on discussing the biological stages and mechanisms of the brain in relation to cognitive functions, students created infographic-based e-Portfolios using Wix AI tools to present neuroscience case studies. They also
designed neuroscience-based products and tools, such as neurofeedback applications and cognitive training solutions, and pitched these innovations through AI-generated videos enriched with animation, voiceovers, and professional storytelling. Together, these activities reinforced
conceptual understanding (CLO2) while deepening students’ ability to critically discuss brain mechanisms in relation to cognitive functions (CLO3), achieving a 100% attainment of CLO3. The outcomes demonstrate increased engagement, creativity, and critical thinking, alongside stronger
digital and AI literacy. Students mastered neuroscience content while cultivating transferable skills in innovation, entrepreneurship, and scientific communication. This initiative highlights the potential of integrating AI-driven platforms into teaching and assessment to create transformative, scalable learning experiences. It also contributes directly to the United Nations Sustainable
Development Goals, including SDG 3: Good Health and Well-being, SDG 4: Quality Education, and SDG 9: Industry, Innovation, and Infrastructure. The project exemplifies how AI-enhanced pedagogy can enrich neuroscience education while advancing transformative education goals at both institutional and global levels
Harnessing AI Innovations for Future-Ready Education in Malaysia Vis-à-Vis Thailand, Singapore and South Korea
No full textThis chapter explores the transformative role of Generative AI technolo-gies in potentially redefining the educational landscape of Malaysia, with compara-tive insights drawn from Thailand, Singapore and South Korea. In the post-COVID-19 era marked by rapid technological change and evolving pedagogical needs, the chapter examines how these nations are integrating AI into their education systems. It critically analyses the impact of AI tools on educators, students and key stake-holders across these countries, highlighting differences in strategy, implementation and outcomes. Special focus is given to the integration of AI in teaching, learning and assessment practices, providing a regional perspective on innovation and inclu-sivity. The chapter also discusses opportunities and challenges faced by Malaysia and its neighbours in adopting AI in classrooms, offering strategic insights for effec-tive and ethical integration. By comparing approaches and outcomes, this chapter provides a roadmap for educators and policymakers to collaboratively steer AI-driven educational reform in Malaysia and beyond. Ultimately, this chapter contributes to the broader discourse on future-ready education in Asia, positioning Malaysia at the forefront of educational innovation in the face of global technological advancements
A systematic literature review of explainable risk assessment models for bronchial asthma
No full textBackground: The reduced quality and risks to life brought on by bronchial asthma (BA) have heightened the need for trustworthy risk assessment solutions with deliberate interpretability and transparency. Improper management of BA, such as ignoring symptoms, improper inhaler technique, or recent admissions to the intensive care unit (ICU), puts a patient at a higher risk of future asthma exacerbations, complications, or even death. This paper details a systematic literature review on recent literature to identify and analyse current explainable artificial intelligence (XAI) risk assessment models used in BA or the assessment of risk in healthcare using XAI.
Methods: A systematic review of English literatures was conducted through Science Direct, Association for Computing Machinery (ACM) Digital Library, Springer, PubMed, and Scopus between January 1, 2019 and October 26, 2023. All studies that incorporated XAI or risk assessment models for BA or health were included for this review. A combination and permutation of the following search terms was used: “explainable artificial intelligence”, “risk assessment”, “risk assessment model”, “asthma”, and “health”.
Results: A total of 43 literatures were included after screening through 689 literatures combined from the specified sources, with duplicates and materials not meeting the inclusion criteria removed. Among them, five of the literatures conducted research on asthma, while seven conducted research on lung-related diseases using explainable machine learning (ML) or deep learning (DL) techniques. The model that had better performance when compared to the other models in the 12 most relevant literature out of the 43 was extreme gradient boosting (XGBoost), with it having better performance two out of the three times it was compared to other models. The most common output was risk prediction with 36 literatures, followed by diagnosis with seven literatures and classification with one.
Conclusions: XAI has been used within the domain of asthma for diagnosis or prediction of future hospital visits; however, there is a scarcity for studies on explainable predictive models for asthma exacerbation risks. Research on XAI within this domain has the potential to contribute towards explainability in asthma risk prediction
Introduction to intelligent biocomposite materials
No full textIntelligent biocomposite materials are developing at the convergence of modern manufacturing and artificial intelligence (AI), through research and the use of natural materials. Natural fibers and renewable bio-based matrices offer a sustainable alternative to traditional undecomposed composites, which exhibit properties such as self-healing, stimulus responsiveness, and environmental adaptation. Therefore, in this chapter, the biocomposite structure, its properties, composition, and correlations were analyzed, including the incorporation of intelligent features that broaden their use across several sectors. Biocomposite development has facilitated its use in various industries, including transportation, building, healthcare, and intelligent packaging. Intelligent biocomposite behavior adapts to temperature, humidity, and stress, improving durability and performance, while self-healing biocomposites address maintenance, environmental, and durability issues. Despite these advances, intelligent biocomposites have challenges in manufacturing scalability, material consistency, and functional quality improvement. The evolving field of AI in biocomposite systems is capable of enhancing material design, enabling real-time monitoring and predicting performance. Therefore this chapter will identify the potential areas and find the critical research gaps for investigation. The crucial materials' green technologies and their importance may enable the global transition to sustainable and intelligent material systems. Lastly, this comprehensive resource chapter aims to provide scholars and industry professionals involved in the next generation of biocomposites by combining existing research, case studies, and new technologies
A Quasi Experimental Study: Cultivating Mathematical Resilience via Intervention in Chinese classrooms
No full textIntroduction: This study evaluates the efficacy of a culturally adapted Chinese Resilience Intervention Module in enhancing mathematical resilience among university students, grounded in the Sidek resilience framework.
Methods: Mathematical resilience was measured using the validated Chinese Mathematical Resilience Scale. The intervention underwent expert validation for cultural and pedagogical relevance. A quasi experimental design compared outcomes between intervention and control groups, with a one month retention test assessing sustainability.
Results: Results demonstrated sustained improvements in resilience scores for the experimental group, persisting through follow up assessments.
Discussion: The findings support the intervention’s potential for identifying at risk learners and informing targeted support strategies in STEM education. Limitations include geographical specificity to Eastern China and short term follow-up. This work advances interdisciplinary approaches to resilience focused pedagogy, advocating for integrated teaching assessment systems to mitigate mathematical learning barriers
The China's Poverty Alleviation Strategies and Its Impacts
No full textEradicating poverty, cultivating a culture of improved livelihood, and attaining shared prosperity are the aspirations and expectations of people around the World. The Communist Party of China (CPC) and the Chinese government have always regarded poverty eradication as important in governing and rejuvenating the country. Under the leadership of the CPC, with President Xi Jinping as its leader, China has adopted innovative reforms and targeted poverty alleviation strategies. After more than eight years of tireless effort, China finally completed the difficult task of eradicating absolute poverty in 2021 and this achievement is significant. This research aims to study the concept and process of China’s poverty alleviation strategies, focusing on innovative theoretical advancement, the challenges and shortcomings within China’s poverty reduction approach. This research is firmly grounded in Marxist theory, using desktop analysis, historical and theoretical research methods, and comparative research methods to explore the theory and practice of China’s poverty alleviation. Using systematic scientific research approaches, the research compiles a comprehensive account of China’s poverty alleviation journey and the multi-dimensional measures undertaken by the CPC to lead poverty alleviation practice across society. The main findings indicated that China’s success story began with the rural poor, who were the backbone of China’s economy. This was followed by targeted poverty measures that focuses on adaptation and innovative approaches into various key sectors (case study of photovoltaic poverty alleviation, health-based interventions and employment-based poverty strategy). Findings indicated that adjustments of policies to socioeconomic changes, and shifting poverty distributions are key to China’s poverty eradication approaches. In short, this study fills the gap in the body of knowledge on China’s efforts on poverty alleviation strategies. It also provides learning model for global poverty eradication strategies. However, the findings are based solely on China’s examples, and therefore, has limited references to international poverty eradication experiences
Promoting mental health among at-risk adolescents in Malaysia (MyHeRo): study protocol for a cluster randomised controlled trial to evaluate the effectiveness and cost-effectiveness of a school-based intervention compared with study skills condition for adolescents identified as at risk for anxiety and depression
No full textAbstract
Background
In Malaysia, adolescent anxiety and depression are increasing faster than ever, and rates of suicidal behaviour are rising especially among those living in deprived communities. However, Malaysia’s mental health system is currently constrained by limited workforce capacity, affecting the delivery of effective interventions. The overall aim of this trial is to use a school-based intervention to promote mental health among at-risk adolescents from low-income communities in Malaysia. Our primary aim is to evaluate the effectiveness and cost-effectiveness of a school-based intervention (“Super Skills for Life”; SSL) in reducing anxiety and depression, and in improving mental wellbeing in adolescents aged 12–14 years. We also aim to determine the characteristics of adolescents who benefit from SSL, compared to those who do not, as well as to identify contextual factors related to the successful implementation of SSL in Malaysian schools.
Methods
The design will be a two-arm, cluster randomised controlled trial comparing school-based intervention (Super Skills for Life; SSL) to study skills control condition (Study Skills Programme; SSP) using a 1:1 allocation ratio. Classrooms will be the cluster unit for randomisation. Three stratification factors will be used for randomisation: school size, classes/forms and school location (urban vs rural). The study will recruit adolescents in at least 20 secondary schools in economically deprived, rural and urban regions in Malaysia. These adolescents will be invited to complete a screening questionnaire (i.e. Depression Anxiety and Stress Scale-21; DASS-21). Based on power calculation, 428 adolescents (214 per arm) who experience moderate to severe levels of anxiety and depression on the DASS-21 will be invited to participate in the trial. Classes will be randomly allocated to SSL or SSP, with eligible adolescents from each class receiving the allocated intervention. Assessment will be conducted at screening, at pre- (i.e. baseline) and post-intervention (i.e. 2 months), and at two follow-ups (i.e. 6 and 12 months post-intervention). The primary outcomes will be a reduction in anxiety and depressive symptoms, and an improvement in mental wellbeing at 12 months post-intervention.
Discussion
Findings of this trial will determine if delivering a group school-based intervention by school staff for adolescents at risk of anxiety and depression is effective and cost-effective. The findings will advance understanding of the role of school staff in the delivery of a school-based intervention and will generate new knowledge on the role of socio-cultural and other contextual factors in predicting intervention uptake and treatment outcome.
Trial registration
ClinicalTrials.gov NCT07138664. Registered on August 16, 2025