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    <link>http://ir.lib.seu.ac.lk/handle/123456789/5</link>
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    <pubDate>Mon, 04 May 2026 16:54:56 GMT</pubDate>
    <dc:date>2026-05-04T16:54:56Z</dc:date>
    <item>
      <title>Assessing Shariah compliance: an analysis of Ijarah financing practices in Sri Lanka's Islamic banking sector against AAOIFI standards</title>
      <link>http://ir.lib.seu.ac.lk/handle/123456789/7921</link>
      <description>Title: Assessing Shariah compliance: an analysis of Ijarah financing practices in Sri Lanka's Islamic banking sector against AAOIFI standards
Authors: Hayathu Mohamed, Ahamed Hilmy; Ahamed Lebbee, Abdul Rauf; Mohamed Casim, Abdul Nazar
Abstract: This study critically examines the extent to which Ijārah nancing practices in&#xD;
Sri Lanka's Islamic banking sector conform to the principles delineated in the Accounting&#xD;
and Auditing Organization for Islamic Financial Institutions (AAOIFI) Shariah Standard&#xD;
No. 9. Employing a qualitative, descriptive, and exploratory methodology grounded in a&#xD;
comprehensive literature review, this study synthesises information from peer reviewed&#xD;
journals, regulatory reports, and institutional documents. It establishes AAOIFI standards&#xD;
as the benchmark for compliance and systematically analyzes Sri Lankan practices,&#xD;
identifying key areas of convergence and divergence. The findings reveal a significant&#xD;
reliance on institutional-level Shariah governance, in the absence of a robust national&#xD;
regulatory framework. The analysis further uncovered critical gaps, particularly in the&#xD;
operational mechanics of Ijārah products, which may functionally resemble conventional&#xD;
nancing in some instances, thereby raising concerns about adherence to the higher&#xD;
objectives of Islamic law (Maqāṣid al-Sharīʿah). This study provides a comparative&#xD;
perspective on international best practices. It offers strategic recommendations for&#xD;
policymakers and financial institutions to enhance Shariah compliance, strengthen&#xD;
transparency, and foster sustainable growth in the Sri Lankan Islamic nance industry.</description>
      <pubDate>Thu, 22 Jan 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://ir.lib.seu.ac.lk/handle/123456789/7921</guid>
      <dc:date>2026-01-22T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Preliminaries</title>
      <link>http://ir.lib.seu.ac.lk/handle/123456789/7920</link>
      <description>Title: Preliminaries</description>
      <pubDate>Thu, 30 Oct 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://ir.lib.seu.ac.lk/handle/123456789/7920</guid>
      <dc:date>2025-10-30T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Assessing urban heat island dynamics in the South Eastern region of Sri Lanka using landsat-8/9 and GIS (2019–2025)</title>
      <link>http://ir.lib.seu.ac.lk/handle/123456789/7919</link>
      <description>Title: Assessing urban heat island dynamics in the South Eastern region of Sri Lanka using landsat-8/9 and GIS (2019–2025)
Authors: Fernando, U. S. D.; Zainudeen, U. L.
Abstract: This study examines the spatiotemporal dynamics of the Urban Heat Island (UHI) effect in &#xD;
the Southeastern region of Sri Lanka, from 2019 to 2025, utilizing Landsat-8/9 satellite &#xD;
imagery and ArcGIS Pro analysis. Despite minimal land use changes, results indicate a &#xD;
significant rise in Land Surface Temperature (LST) from 36.31 °C in 2019 to 37.54 °C in &#xD;
2025, with Urban Heat Island Intensity (UHII) increasing from 0.009172 to 0.01159. &#xD;
Supervised classification revealed a decline in vegetation cover (NDVI from +0.81 to -0.13) &#xD;
and an increase in urban (9% to 16%) and bare land (2% to 15%) areas, correlating with &#xD;
elevated LST and UHII, particularly during dry seasons. Albedo measurements using a lux &#xD;
meter showed low reflectivity (0.055-0.278) for urban surfaces like roads and concrete, &#xD;
enhancing heat retention, while paddy fields (0.07-0.11) contributed to temperature rises &#xD;
under reduced moisture. It indicates Sammanthurai has low albedo surface and it causes to &#xD;
rice temperature of the area. Weather data from 2024 highlighted a peak temperature of 38.7 &#xD;
°C, with a weak positive correlation (slope 0.02) between solar radiation (224.64 W/m²) and &#xD;
temperature, exacerbating UHI effects. Comparative analysis with Kitulgala’s wetter, &#xD;
forested region (207.065 W/m², 24-31 °C) underscores the role of vegetation and climate in &#xD;
mitigating heat. The study, achieving 91% classification accuracy (Kappa 0.88541), &#xD;
emphasizes climatic factors and land management as key drivers of UHI in semi-rural, &#xD;
agrarian landscapes.</description>
      <pubDate>Thu, 30 Oct 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://ir.lib.seu.ac.lk/handle/123456789/7919</guid>
      <dc:date>2025-10-30T00:00:00Z</dc:date>
    </item>
    <item>
      <title>A custom Python script for automated tracking of locomotor activity in amphibian larvae</title>
      <link>http://ir.lib.seu.ac.lk/handle/123456789/7918</link>
      <description>Title: A custom Python script for automated tracking of locomotor activity in amphibian larvae
Authors: Rajapaksha, H. T. D.; Dissanayake, B. M.; Wickramasinghec, W. A. G. K.; Pathirana, N. U. K.
Abstract: Automated behavioural tracking tools are increasingly valuable for reducing observer bias, &#xD;
improving reproducibility, and enabling high-throughput data collection in animal behaviour &#xD;
research. Recent developments in open-source and customizable tracking platforms have &#xD;
enhanced accessibility and analytical efficiency across species, while modern programming &#xD;
tools like R and Python enable affordable and precise behavioural quantification, particularly &#xD;
valuable for research in resource-limited settings. Existing commercial and open-source &#xD;
packages provide useful frameworks, yet they are often constrained by limited flexibility, &#xD;
high costs, or inadequate adaptability to species-specific behaviours, particularly in non- &#xD;
model organisms such as amphibian larvae. To address this gap, we developed a custom &#xD;
Python-based tracking script capable of quantifying locomotor activity from standard video &#xD;
recordings The tool automates the detection and tracking of individual larvae, extracting &#xD;
continuous X–Y positional data and generating visual outputs such as trajectory plots and &#xD;
heat maps to represent spatial activity patterns. Output files are produced in Excel- &#xD;
compatible format, allowing seamless integration with statistical workflows. Behavioral &#xD;
trials were conducted to evaluate both short-term repeatability and developmental &#xD;
consistency of locomotor traits in tadpoles, demonstrating the script’s ability to capture fine- &#xD;
scale variation in activity levels over time. Preliminary validation against manual scoring &#xD;
confirmed high accuracy and reliability, highlighting its potential as a robust alternative to &#xD;
observer-based measurements. Importantly, the script’s open and adaptable structure allows &#xD;
researchers to modify tracking parameters according to study needs, extending its &#xD;
applicability beyond amphibians to other small aquatic organisms. This custom tool &#xD;
therefore offers a flexible, low-cost, and reproducible approach for behavioural ecologists &#xD;
and conservation biologists investigating movement and activity in larval stages. By &#xD;
facilitating detailed and standardized quantification of locomotion, it contributes to &#xD;
advancing questions in developmental biology, personality research, and ecological &#xD;
assessments of amphibian populations—areas of growing significance in light of global &#xD;
amphibian declines.</description>
      <pubDate>Thu, 30 Oct 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://ir.lib.seu.ac.lk/handle/123456789/7918</guid>
      <dc:date>2025-10-30T00:00:00Z</dc:date>
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