Search Results (105)

The functionalization of molecules on C₆₀ is a promising engineering approach, as non-covalently governed fullerene surfaces facilitate reversible host–guest recognition, tunable electronic communication, and conformationally adaptive molecular adsorption. In this work, spin-resolved simulations using density functional theory (DFT) were conducted to examine the interaction between a newly identified arylalkanone isolated from the medicinal species Myristica ceylanica and the nanocarbon framework of C₆₀ fullerene, including doped configurations incorporating group III elements (B, Al, Ga, In and Tl). The results indicate that the arylalkanone binds to pristine C₆₀ through an exothermic, energetically favourable binding process, supporting thermodynamically viable molecular uptake. Among the doped models, B substitution exhibits the greatest overall thermodynamic preference; however, Al doping produces the most pronounced enhancement in binding energy, identifying the Al-doped configuration as the most effective surface-uptake architecture in relative terms. Across all complexes, a small amount of charge transfer is noted, signifying weak yet persistent electronic coupling between the ligand and the carbon carrier. Additionally, all doped fullerenes demonstrate induced magnetic behaviour, a property of increasing relevance in spintronics research, suggesting that these complexes may hold future value in spin-dependent electronic and molecular-recognition-guided nanoscale biomedical engineering. Full article

A phytochemical investigation of Myristica ceylanica resulted in the identification of seven arylalkanone-derived phenolic compounds, comprising one new naturally occurring arylalkanone (A), two derivatives (A₁ and A₂) prepared by chemical synthesis, and four known malabaricones (B–E). Density functional theory (DFT) calculations were conducted to evaluate the geometries, electronic properties, and charge distributions of the newly identified arylalkanone and its derivatives and to compare them with those of malabaricones B–E. The arylalkanones exhibited geometrical features comparable to those of the malabaricones, whereas frontier molecular orbital analysis revealed similar HOMO–LUMO energy gaps for the malabaricones but a progressive widening of the gap among the arylalkanone derivatives, indicating enhanced electronic stabilisation. Mulliken population analysis identified oxygen atoms as the principal electron-rich sites in both series, with arylalkanones displaying greater charge polarisation and increased sensitivity to structural substitution. Full article

Aramid Fiber Reinforced Plastic (AFRP) and aluminum alloy Al7075-T6 are widely used in the aerospace industry because they offer a high strength-to-weight ratio and reliable structural performance. However, drilling through stacked AFRP and Al7075-T6 materials in a single operation presents considerable challenges due to the differences in their mechanical and thermal properties. In this study, three types of customized twist drill bits were designed and fabricated to evaluate their effectiveness in single-shot drilling of these stacked materials. The drill geometries included the W-point design, the tapered web design, and the burnishing design. Each drill bit was tested using its own optimized drilling parameters to produce a total of one hundred holes. The aim was to determine which drill geometry provided the best overall performance in terms of tool wear and hole quality. After the drilling experiments, the tool tips were examined using a Scanning Electron Microscope (SEM) to observe wear characteristics and analyze elemental composition. The analysis revealed that aluminum adhered to the cutting lips of all drill bits. The percentage of adhesion layer, known as percentage of adhesion layer (PAL), was calculated to assess the severity of material adhesion. In addition, the morphology of the produced chips and dust was analyzed to support the PAL results. The findings showed that the drill bit with the lowest PAL value demonstrated superior wear resistance, a longer tool life, and the ability to produce holes of higher quality when drilling AFRP and Al7075-T6 stacked materials. Full article

Rechargeable sodium-ion batteries (SIBs) have attracted considerable attention owing to the natural abundance and accessibility of sodium. Maricite NaMnPO₄, a phosphate-based cathode material with high theoretical capacity, suffers from blocked sodium-ion diffusion channels. In this study, atomistic simulations using pair potentials and density functional theory (DFT) are employed to investigate intrinsic defect mechanisms, sodium-ion migration pathways, and the role of dopant incorporation at Na, Mn, and P sites in generating Na vacancies and interstitials. Among the intrinsic defects, the Na–Mn anti-site cluster emerges as the most favorable, exhibiting a very low formation energy of 0.12 eV, while the Na Frenkel pair (1.93 eV) is the next most stable defect, indicating that sodium diffusion is primarily facilitated by vacancy formation. Nevertheless, sodium-ion mobility in NaMnPO₄ remains limited, as reflected by the relatively high migration activation energy of 1.28 eV. Among the isovalent substitutions, K is predicted to be the most favorable dopant at the Na site, whereas Ca and Cu are the most favorable at the Mn site. Thallium is identified as a promising dopant at the Mn site for generating Na vacancies that facilitate Na-ion migration, while Ge substitution at the P site is predicted to enhance the sodium content in the material. Full article

Late-stage cancer diagnoses of prevalent cancers are increasing in the Northern Province of Sri Lanka, a region currently rebuilding its healthcare system after a prolonged civil war. In this region, cancer prevention services are limited. We describe a community-centric approach to cancer education and prevention as a strategy to cancer control in this rural, post-conflict region. Nursing students were trained as Community Cancer Educators (CCEs), equipping them with essential knowledge about cancer symptoms, risk factors, and the importance of early detection. The training also included creative methods such as dance and drama to help CCEs communicate cancer-related messages in an engaging and culturally relevant manner. These CCEs supported the oncologist-led community health camps in delivering cancer education and screening directly to community members within their community. We planned the health camps in collaboration with the existing community-based public health system for better outreach. Feedback from community participants and healthcare providers suggests that this community-centric approach can improve cancer awareness, encourage participation in population screening, and support early cancer detection. This approach could strengthen community engagement and contribute to more equitable access to prevention and screening services in rural, post-conflict settings with limited healthcare infrastructure. Full article

The accurate measurement of herbage mass is essential for feed budgeting and the management of sustainable and profitable grazing systems. There are many techniques available to estimate herbage mass in pastoral systems, and these vary in accuracy, cost, and time taken to implement. In situ and remote sensing techniques are both associated with moderate to high error, as herbage mass is affected by a number of dependent and independent factors, including sward composition, soil structure, chemical characteristics and moisture levels, climatic conditions, and grazing management, which must be considered in the development of an accurate local calibration model for precise estimation of herbage mass. This review provides an overview of commonly used herbage mass assessment techniques and describes their limitations, synergies, and trade-offs, and also covers the integration of new technologies which have the potential to monitor pastures at scale. This review highlights the need for further research and to integrate new technologies for accurate and precise measurement of herbage mass, noting the lack of calibration with in situ methods, the need for development of new protocols for assessment, variance in equipment and software compatibility, and the need to evaluate the effectiveness of methods/techniques on a variety of livestock operations for extended periods. Full article

Mangroves in Sri Lanka provide critical ecosystem services, yet they have undergone significant changes due to anthropogenic and natural drivers. This study presents the first national-scale assessment of mangrove dynamics in Sri Lanka using remote sensing techniques. A total of 4670 Landsat images from Landsat 5, 7, 8, and 9 were selected to detect mangrove distribution, changes in extent, and structure and stability patterns from 1987 to 2022. A Random Forest classification model was applied to elucidate the spatial changes in mangrove distribution in Sri Lanka. Using national-scale data enhanced mapping accuracy by incorporating region-specific spectral and ecological characteristics. The average overall accuracy of the maps was over 96.29%. The total extent of mangroves in 2022 was 16,615 ha, representing 0.25% of the total land of Sri Lanka. The results further indicate that, at the national scale, mangrove extent increased from 1989 to 2022, with a net gain of 1988 ha (13.6%), suggesting a sustained and continuous recovery of mangroves. Provincial-wise assessments reveal that the Eastern and Northern Provinces showed the largest mangrove extents in Sri Lanka. In contrast, the Colombo, Gampaha, and Kalutara districts in the Western Province showed persistent declines. The top mangrove spatial structure and stability districts were Jaffna, Trincomalee, and Gampaha, while the most degraded mangrove districts were Batticaloa, Colombo, and Kalutara. This study offers critical insights into sustainable mangrove management, policy implementation, and climate resilience strategies in Sri Lanka. Full article

Background and Objectives: The relationship between ABO or Rh blood groups and susceptibility to Chikungunya virus (CHIKV) infection remains unclear. This systematic review and meta-analysis aimed to synthesize available evidence on this association. Materials and Methods: Studies reporting ABO and/or Rh blood groups and CHIKV infection were searched through PubMed, Scopus, EMBASE, MEDLINE, Ovid, ProQuest, and Google Scholar up to 8 July 2025. A random-effects meta-analysis was conducted to calculate pooled odds ratios (Ors) with 95% CIs. Heterogeneity was assessed using I² statistics. Subgroup analyses were performed based on study design and study quality. Sensitivity analysis was conducted using a leave-one-out method. Publication bias was evaluated via funnel plots and Egger’s test. Results: Seven studies, including 24,828 participants, were included. No significant associations were observed between blood groups A, B, AB, or Rh(D) and CHIKV infection. However, blood group O was significantly associated with an increased risk of CHIKV infection (OR: 1.52, 95% CI: 1.01–2.29, p = 0.043, I² = 95.38%) compared to non-O blood groups. Subgroup analyses showed stable results. Nevertheless, the sensitivity analysis indicated that certain studies had a greater influence on the overall results. In addition, significant publication bias was also detected. Conclusions: Current evidence indicates that blood group O is significantly associated with an increased susceptibility to CHIKV infection. In contrast, no consistent associations were observed for other ABO or Rh blood groups. Due to substantial heterogeneity and methodological limitations, these findings should be interpreted with caution. Further well-designed, large-scale studies with standardized diagnostics are needed to clarify these associations and underlying mechanisms. Full article

This study employs density functional theory (DFT) to investigate the electronic and optical properties of molybdenum (Mo) and chalcogen (S, Se, Te) co-doped anatase TiO₂. Two co-doping configurations were examined: Model 1, where the dopants are adjacent, and Model 2, where the dopants are farther apart. The incorporation of Mo into anatase TiO₂ resulted in a significant bandgap reduction, lowering it from 3.22 eV (pure TiO₂) to range of 2.52–0.68 eV, depending on the specific doping model. The introduction of Mo-4d states below the conduction band led to a shift in the Fermi level from the top of the valence band to the bottom of the conduction band, confirming the n-type doping characteristics of Mo in TiO₂. Chalcogen doping introduced isolated electronic states from Te-5p, S-3p, and Se-4p located above the valence band maximum, further reducing the bandgap. Among the examined configurations, Mo–S co-doping in Model 1 exhibited most optimal structural stability structure with the fewer impurity states, enhancing photocatalytic efficiency by reducing charge recombination. With the exception of Mo–Te co-doping, all co-doped systems demonstrated strong oxidation power under visible light, making Mo-S and Mo-Se co-doped TiO₂ promising candidates for oxidation-driven photocatalysis. However, their limited reduction ability suggests they may be less suitable for water-splitting applications. The study also revealed that dopant positioning significantly influences charge transfer and optoelectronic properties. Model 1 favored localized electron density and weaker magnetization, while Model 2 exhibited delocalized charge density and stronger magnetization. These findings underscore the critical role of dopant arrangement in optimizing TiO₂-based photocatalysts for solar energy applications. Full article

Individual tree crown detection (ITCD) and tree species classification are critical for forest inventory, species-specific monitoring, and ecological studies. However, accurately detecting tree crowns and identifying species in structurally complex forests with overlapping canopies remains challenging. This study was conducted in a complex mixed conifer–broadleaf forest in northern Japan, aiming to improve ITCD and species classification by employing two machine learning models and different combinations of metrics derived from very high-resolution (2.5 cm) UAV red–green–blue (RGB) and multispectral (MS) imagery. We first enhanced ITCD by integrating different combinations of metrics into multiresolution segmentation (MRS) and DeepForest (DF) models. ITCD accuracy was evaluated across dominant forest types and tree density classes. Next, nine tree species were classified using the ITCD outputs from both MRS and DF approaches, applying Random Forest and DF models, respectively. Incorporating structural, textural, and spectral metrics improved MRS-based ITCD, achieving F-scores of 0.44–0.58. The DF model, which used only structural and spectral metrics, achieved higher F-scores of 0.62–0.79. For species classification, the Random Forest model achieved a Kappa value of 0.81, while the DF model attained a higher Kappa value of 0.91. These findings demonstrate the effectiveness of integrating UAV-derived metrics and advanced modeling approaches for accurate ITCD and species classification in heterogeneous forest environments. The proposed methodology offers a scalable and cost-efficient solution for detailed forest monitoring and species-level assessment. Full article

The objective was to conduct a review and meta-analysis of questionnaire-based surveys of dengue knowledge, attitudes, perceptions, and practices (KAP)s among the general public in Sri Lanka as no prior island-wide survey existed. The electronic database PubMed and other bibliography were searched for literature on dengue questionnaire-based KAP surveys in Sri Lanka from 2000–2023. Data pertaining to the three domains were extracted from sixteen eligible articles, pooled, and analyzed separately using random effect models. Meta-analyses of the three domains were performed using R version 3.6.3. The population surveyed (8955) was <0.045% of the total Sri Lankan population. The publication frequency increased over time and surveys were distributed in Colombo and suburbs 43.7% (7/16), Kandy 25% (4/16,) Gampaha 12.5% (2/16), and 6.3% (1/16) one each in Kurunegala, Matara, Batticaloa, and Jaffna. Knowledge on dengue transmission, vector breeding, and fever as a symptom was >80%, while on vector species, preferred feeding times, recurrence of dengue it was > 55% and on warning signs of severity it was 25%. Attitudes towards community participation in dengue prevention activities and knowledge of dengue risk factors (avoidance of aspirin and dark colored drinks) were poor, while practice of control measures (removal of water collecting receptacles, roof-gutter management) lacked regularity. Full article

Salicornia brachiata Roxb., an economically and ecologically significant halophytic species native to Sri Lanka, produces dimorphic seeds. Despite their importance for commercial cultivation and conservation, germination studies of these dimorphic seeds remain limited. This study investigated the effects of temperature (25 °C, 30 °C, 35 °C), gibberellic acid (GA₃) treatment, geographic location of seed source (Jaffna vs. Puttalam coastal regions), seed type (central vs. lateral), and perianth presence/absence on germination under controlled conditions. Our results show that temperature, GA₃, and geographic location of the seed source significantly influenced seed germination. This study presents the first documented evidence of physiological dormancy (PD) in S. brachiata seeds, with successful dormancy breaking achieved using GA₃ treatment at 25 °C. Although perianth and seed type alone had no significant direct effects on germination, they were involved in multiple significant interactions—two-, three-, and four-way—with other factors. These findings highlight the multifactorial regulation of S. brachiata seed germination, suggesting that tailored propagation strategies, incorporating environmental and physiological variables, can optimize germination. These findings offer practical solutions for enhancing germination in saline agriculture and habitat restoration efforts of S. brachiata. Full article

This review offers an in-depth analysis of soil contamination, discussing the origins, impacts, and remediation strategies, as well as the complex connections with interfacial chemistry. Interfacial chemistry plays a critical role in addressing soil contamination by governing the interactions between pollutants, soil particles, water, and remediation agents at phase boundaries (solid–liquid, solid–gas). Some key aspects include adsorption/desorption that controls pollutants binding to soil surfaces; chemical transformation which facilitates redox, hydrolysis, or catalytic reactions at interfaces to degrade contaminants; colloidal transport that affects the movement of nanoparticle-bound contaminants through soil pores; and techniques like soil washing, phytoremediation and permeable reactive barriers that can neutralize soil pollutants. The combination of interfacial chemistry and soil remediation techniques offers rich opportunities for improving predictive models of contaminant fate. Such approaches represent a paradigm shift from equilibrium-based remediation to dynamic process management. The review demonstrates how heterogeneous interfaces and molecular-scale dynamics dictate contaminant behavior. Furthermore, in addition to consolidating existing knowledge, the review also pioneers new directions by revealing how interfacial processes can optimize soil decontamination, offering actionable insights for researchers and policy makers. By understanding and manipulating interfacial chemical processes, scientists can develop more precise and sustainable cleanup methods. Full article

Assistive technology (AT) is increasingly utilized across various sectors, including digital healthcare and sports education. E-learning plays a vital role in enabling students with special needs, particularly those in remote areas, to access education. However, as the adoption of AI-based AT systems expands, the associated cybersecurity challenges also grow. This study aims to examine the impact of AI-driven assistive technologies on cybersecurity in digital healthcare applications, with a focus on the potential vulnerabilities these technologies present. Methods: The proposed model focuses on enhancing AI-based AT through the implementation of emerging technologies used for security, risk management strategies, and a robust assessment framework. With these improvements, the AI-based Internet of Things (IoT) plays major roles within the AT. This model addresses the identification and mitigation of cybersecurity risks in AI-based systems, specifically in the context of digital healthcare applications. Results: The findings indicate that the application of the AI-based risk and resilience assessment framework significantly improves the security of AT systems, specifically those supporting e-learning for blind users. The model demonstrated measurable improvements in the robustness of cybersecurity in digital health, particularly in reducing cyber risks for AT users involved in e-learning environments. Conclusions: The proposed model provides a comprehensive approach to securing AI-based AT in digital healthcare applications. By improving the resilience of assistive systems, it minimizes cybersecurity risks for users, specifically blind individuals, and enhances the effectiveness of e-learning in sports education. Full article

Concerns about sustainable energy sources arise due to the non-renewable nature of petroleum. Escalating demand for fossil fuels and price inflation negatively impact the energy security and economy of a country. The generation and usage of biofuel could be suggested as a sustainable alternative to fossil fuels. Several studies have investigated the potential of using edible crops for biofuel production. However, the usage of algae as suitable feedstock is currently being promoted due to its ability to withstand adverse environmental conditions, capacity to generate more oil per area, and potential to mitigate energy crises and climate change with no detrimental impact on the environment and food supply. Furthermore, the biorefinery approach in algae-based biofuel production controls the economy of algal cultivation. Hence, this article critically reviews different cultivation systems of algae with critical parameters including harvesting methods, intended algae-based biofuels with relevant processing techniques, other applications of valorized algal biomass, merits and demerits, and limitations and challenges in algae-based biofuel production. Full article