Publications by authors named "S H S Karunaratne"

The microbial pollution status of river surface water is important to ensure a river-based quality drinking water supply for the public. The present study aimed to investigate bacterial contamination status in the upper Mahaweli River, the main drinking water supplier to the hill country of Sri Lanka. Both the raw surface water and treated water, taken at 14 drinking water treatment plants (DWTPs) along the river segment of 60 km between Kotmale and Victoria reservoirs, were tested for total bacterial counts (TBC), total coliform counts (TCC) and faecal coliform counts (FCC).

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Background: Pelvic mucosal melanomas, including anorectal and urogenital melanomas, are rare and aggressive with a median overall survival of up to 20 months. Pelvic mucosal melanomas behave differently to its cutaneous counterparts and presents late with locoregional disease, making pelvic exenteration its only curative surgical option.

Objective: This study aimed to evaluate the survival outcomes post pelvic exenteration in pelvic mucosal melanomas at Royal Prince Alfred Hospital.

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confocal microscopy (IVCM) is a widely used technique for imaging the cornea of the eye with a confocal scanning light ophthalmoscope. Cellular resolution and high contrast are achieved without invasive procedures, suiting the study of living humans. However, acquiring useful image data can be challenging due to the incessant motion of the eye, such that images are typically limited by noise and a restricted field of view.

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Radiological embolisation has emerged as a safe and effective alternative to surgery for varicocele treatment. While systematic reviews have compared embolisation to surgery, attempts to compare different embolisation materials have been limited. The objective was to conduct a systematic review assessing the potential benefits of combining coils with sclerosants for varicocele embolisation on fertility, pain, recurrence and complication rates in male patients, as compared to using coils alone.

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This study investigated the dynamics of land use and land cover (LULC) modelling, mapping, and assessment in the Kegalle District of Sri Lanka, where policy decision-making is crucial in agricultural development where LULC temporal datasets are not readily available. Employing remotely sensed datasets and machine learning algorithms, the work presented here aims to compare the accuracy of three classification approaches in mapping LULC categories across the time in the study area primarily using the Google Earth Engine (GEE). Three classifiers namely random forest (RF), support vector machines (SVM), and classification and regression trees (CART) were used in LULC modelling, mapping, and change analysis.

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